Oblique Markets

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description must carry the full burden of disclosing side effects, requirements, and safety. It mentions pricing, handoff, and receipt binding, which hint at behavior, but these are unexplained jargon. It does not state whether the operation is read-only, what resources are consumed, or what the consequences are. The 'ghost-bid counterfactual pricing' and 'qualified handoff' are opaque, and the tool's actual effect is unclear.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single dense sentence that packs in multiple concepts without prioritization. It is not front-loaded with the most critical information (what it does and when to use it) and is heavy with domain-specific jargon that obscures rather than clarifies. Appropriately sized but poorly structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 8 parameters, 0% schema coverage, no annotated safety profile, and no output schema, the description is grossly insufficient. It fails to explain the return format, the meaning of most parameters, the difference between the free and paid tiers, and the routing mechanism. An agent would be unable to call this tool correctly without substantial additional information from elsewhere.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must explain the parameters. It only hints at pricing (free vs. paid) and mention of 'receipt binding' may relate to seller_delivery_receipt, but it does not map parameters like max_price, price_cap, constraints, output_format, or preferred_rail to specific meanings. The description adds minimal value over the raw parameter names.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource ('task router') but is vague about what routing entails and doesn't differentiate it from sibling tools like route_task or mpp_route. It mentions pricing options but doesn't clarify the core output or behavior, making the purpose only partially clear.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus the sibling routers (route_task, mpp_route). The description does not mention any context, conditions, or exclusions, leaving the agent to guess which router fits a given task.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations exist, so the description carries the behavioral disclosure burden. It does add useful context: the call costs $0.005 via x402 and the response yields statuses, an evidence hash, and a bundle ID. However, it does not disclose whether the operation is read-only, how endpoint_verify executes, whether defaults apply, or any authentication/rate-limit constraints.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence with no significant wasted words. The word 'proven' is mild promotional fluff, but the core behavior, scope, outputs, and pricing are all present.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has eight parameters, one nested object parameter, and no output schema. The description names the top-level outputs but not their structure or the default behavior of running all components. The schema covers parameter meanings well, but the description alone does not fully specify how the bundle behaves for an agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the parameters are already documented in the input schema. The description adds only the 'up to five' selection constraint and the general output shape, not new semantic meaning for individual parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific action: selecting up to five time, Base, wallet-balance, and x402 verification utilities into a single preflight bundle, and lists key outputs (statuses, evidence hash, bundle ID). It reads as a bundle tool, which distinguishes it from individual sibling utilities, though it never explicitly names those alternatives.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance on when to use this tool versus the individual base_block_number, base_usdc_balance, server_time, x402_endpoint_verify, or b402_preflight siblings. The bundling phrasing implies an aggregation use case, but no explicit when/when-not or alternative routing is provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the behavioral burden. It does disclose the $1.00/call monetization, which is a genuine economic trait. However, it does not cover failure modes, rate limits, or behavior on invalid/non-AI domains, and the normalization detail lives in the schema rather than here.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

One dense sentence that front-loads the action, explicitly enumerates the audited surfaces, and lists all return components. The cost is tacked on cleanly at the end. Minimal waste, though the missing usage guidance is an absence rather than a conciseness issue.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a single-parameter tool with no output schema, it reasonably covers the audit scope, output constituents (score, missing fields, findings, prioritized fixes), and cost. It would be more complete if it distinguished itself from the overlapping x402/b402 siblings, but it is adequate for invoking correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and the single 'domain' parameter is already well described (bare domain or https URL, normalized to https origin). The description adds cost context but no parameter-specific semantics, so the baseline 3 for full schema coverage is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb (verify) and a specific resource (AI Agent API discovery surfaces: x402, agent.json, OpenAPI, llms.txt, robots.txt, MCP), and lists concrete outputs. It is clear about what it does, though it does not explicitly contrast with the narrower sibling tools (x402_endpoint_verify, b402_preflight), so differentiation is implicit rather than stated.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this audit versus its siblings (x402_endpoint_verify, b402_preflight, fetch_x402_content). It does mention the $1.00/call cost, which hints at a decision factor, but there are no exclusions or alternative routing, leaving the agent to infer when the breadth of this audit is warranted.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full behavioral burden and does reasonably well: it discloses the bounded nature, accountless scope, cursor-aware behavior, included result categories, evidence hash, and exact per-call cost via x402. It could be clearer about side effects or error behavior, but for a context-bundle retrieval tool this is solid.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single dense sentence that front-loads the core purpose and packs in scope, optional content, and pricing without filler. It is efficient, though the jargon density slightly hurts readability.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with no annotations and no output schema, the description covers cost, optional components, cursor-awareness, and key return elements. However, terms like 'bounded', 'accountless', and 'evidence hash' are left unexplained, and there is no explicit guidance on edge cases or expected output shape beyond the listed bundle elements.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The description adds some value by mapping the bundle contents to cursor-aware Bazaar delta/trending and next cursor, but it does not meaningfully elaborate beyond the schema's own parameter descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb and resource: it gives a returning agent a bounded accountless context bundle. It further specifies what the bundle can contain — cursor-aware Bazaar delta/trending results, statuses, next cursor, and evidence hash — which clearly distinguishes it from generic bundle or Bazaar-only siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It implies use for returning agents needing a bounded, accountless context bundle with cursor-aware Bazaar data, and the pricing signals x402 usage. However, it does not explicitly state when to use this tool versus siblings like agent_preflight_bundle, bazaar_delta, or bazaar_trending, nor does it mention exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description must carry the behavioral burden. It mentions the cost per call ($0.65 via x402), which is a practical behavioral trait, and implies it performs web research with citations. However, it does not disclose limitations (e.g., timeouts, source reliability, failure modes) or what exactly constitutes an 'evidence packet'. It adds some value beyond the schema but lacks depth.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence followed by a pricing note. It is perfectly concise, front-loaded with the action, and contains no fluff. Every part earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (one required parameter) and the absence of an output schema, the description covers the core behavior sufficiently. It names the output components (cited sources and evidence packet) though not the exact structure. This is adequate for an agent to know what it will receive, though it could benefit from mentioning pagination or formatting.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema coverage is 100%; the 'question' parameter is described as 'Question to answer with citations'. The tool description adds no extra semantics beyond that, such as expected format, length, or examples. With high schema coverage, the baseline is 3, and the description does not exceed it.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'answer' and the resource 'research question', and specifies the output as 'cited web sources' and a 'concise evidence packet'. It is specific enough to distinguish it from generic web extraction or keyword tools, though it doesn't explicitly name a sibling alternative. This fits a 4: clear purpose without explicit sibling differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives no guidance on when to use this tool versus alternatives like web_extract or company_research. It does not state any conditions, exclusions, or recommended scenarios. The context of answering a research question is implied but not contrasted with other tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Despite having no annotations, the description discloses key behavioral traits: it performs validation without custody or payment relay, indicating a non-mutating read operation. It also mentions checking public BNB balance and recent activity, which implies on-chain reads, and discloses a cost of $0.01/call. However, it does not explicitly call itself read-only or describe error handling, leaving some ambiguity about side effects beyond 'without custody'.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, well-structured sentence that front-loads the verb and resource, lists validation targets, and concludes with a cost note. It is under 30 words with no redundant information, making it highly economical and easy to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For an 8-parameter tool with no annotations and no output schema, the description provides a solid overview of what is validated but omits details about return values, error conditions, and inter-parameter relationships (e.g., chain/asset compatibility). It does not mention prerequisites or limitations beyond 'without custody,' leaving some ambiguity for an agent that needs to handle errors or interpret results.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is only 38% (only asset, fee_cap, and deadline have descriptions). The description lists validation aspects that map to parameters (freshness → deadline, recipient → recipient, amount → amount, fee cap → fee_cap, balance → payer) but does not add detailed semantics for each parameter. It partially compensates by connecting parameters to the validation purpose, but it leaves intent_id and payer (beyond pattern) under-explained, and does not fully cover the gaps in the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool validates BNB/B402 payment intents, listing specific aspects to validate (freshness, recipient, amount, deadline, fee cap, public BNB balance, recent activity) and explicitly excludes custody and payment relay. This distinguishes it from sibling tools like x402_endpoint_verify and x402_receipt_lookup, which focus on different stages of the x402 lifecycle.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description does not provide explicit guidance on when to use this tool versus alternatives. It does not name sibling tools or specify conditions for selection. The name 'preflight' implies it is used before initiating a payment, but this is not stated, and no 'when-not' or alternative routing advice is given. With no annotations to compensate, the description leaves usage context to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

There are no annotations, so the description carries the full disclosure burden. It adds meaningful behavioral detail: data is fetched from redundant public RPCs, results include source and freshness metadata, and each call costs $0.002 via x402. It does not enumerate failure modes or rate limits, but this is a simple read-only fetch and the disclosed information is sufficient.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two concise sentences with no filler. The action and resource are front-loaded, and the pricing detail is appended as an efficient second sentence.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter read-only fetch, the description supplies enough: purpose, data source, return nature, and cost. It does not specify exact JSON field names, and there is no output schema, so a bit more detail about the returned structure could have improved it, but selection and invocation remain unambiguous.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters and the input schema is an empty object, so there is nothing for the description to clarify about parameter meanings. The baseline of 4 applies because the parameter surface is empty.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific operation (fetch), resource (current Base mainnet block number), data source (redundant public RPCs), and output shape (structured JSON with source and freshness metadata). This makes it immediately distinguishable from sibling tools like base_gas_price and base_tx_status.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description clearly establishes when the tool is appropriate: when the current Base mainnet block number is needed. It does not explicitly list alternative tools or exclusion conditions, but the specificity of the resource provides clear selection context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Discloses source (redundant public RPCs) and pricing ($0.002/call), but does not mention read-only nature, error handling, caching, or rate limits. Since annotations are absent, this is a partial disclosure.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

One compact sentence packs the resource, output fields, source, and cost. It is front-loaded with the primary purpose and avoids fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter tool, it fully specifies the output (gas price, base fee, block number, timestamp), the source, and cost. No output schema exists, so this description serves as the agent's complete reference.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

No parameters exist, so the description adds nothing beyond the empty schema. Baseline 4 applies because the tool requires no input parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States exactly what it returns: current Base gas price, EIP-1559 base fee in wei and gwei, plus block number and timestamp. This clearly distinguishes it from sibling tools like base_block_number by focusing on gas price and fees.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives. It doesn't mention when to avoid it or which sibling covers other use cases, such as block number only. The cost note is informational but not a usage criterion.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden for behavioral disclosure. It does disclose useful traits: bounded results, Arkham-compatible normalization, and a $0.005/call x402 cost. However, it does not explain prerequisites such as x402 payment setup, response contents, failure behavior, or pagination limits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single concise sentence with no wasted words. It front-loads the core scope and includes the cost detail at the end. This is an appropriately sized description for the amount of information provided.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a six-parameter paid tool with no output schema and no annotations, the description is too terse. It omits payment/auth prerequisites, pagination behavior, output shape, and the relationship to the direct sibling base_transfer_search_rpc. An agent cannot fully determine correct invocation from this description alone.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description needs to compensate for the six parameters. It only lists 'chain, token, flow, pagination' without definitions, and it does not explain that `chains` is restricted to `base`, that `flow` accepts in/out/all, or how `limit` and `offset` work. The schema enums help, but the description does not add enough parameter-level meaning.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states that the tool returns Arkham-compatible bounded Base ERC-20 transfer results for one wallet, clearly indicating a search/list operation despite lacking an explicit verb. It names chain, token, flow, pagination, and normalized fields, which helps differentiate it from generic transfer tools. It does not explicitly name its sibling base_transfer_search_rpc, but the Arkham-compatibility and normalization phrasing provide partial differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives no guidance on when to use this tool versus the sibling base_transfer_search_rpc or other wallet/transfer tools. It mentions cost and boundedness but does not state conditions, exclusions, or alternatives. The agent is left to infer the appropriate usage context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden. It does disclose that the search is bounded, that it returns structured transfer records, and that each call costs $0.02 via x402. However, it does not explain behavior such as default limits, ordering, pagination, or what 'bounded' precisely means, so transparency is only partial.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single concise sentence that front-loads the core purpose and then adds the pricing detail. Every part earns its place, and there is no redundant or filler content.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 7-parameter tool with no output schema and no annotations, the description is reasonably informative but not complete. It does not explain the required direction and address parameters, limit defaults, timestamp constraints, or the relationship to the sibling base_transfer_search. Still, enough high-level context is present for the tool to be used plausibly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It names five filter dimensions: address, direction, asset, counterparty, and time window. This adds meaning beyond the bare schema, but it does not clarify the semantics of each parameter in detail, such as direction relative to the address or the meaning of the limit parameter.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description gives a specific verb ('Search'), a concrete resource ('Base mainnet ERC-20 transfers'), and the filter dimensions used. It is clear and understandable on its own. However, it does not differentiate this tool from the sibling base_transfer_search, so it misses the explicit sibling distinction needed for a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies the tool is for searching ERC-20 transfers, but it provides no guidance about when to prefer this tool over alternatives. Most importantly, there is a closely named sibling 'base_transfer_search' with no stated distinction, leaving the agent without routing guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses the cost model ($0.003/call via x402) and lists the returned data fields, which is useful. However, it does not explicitly state that this is a read-only operation or mention any failure modes or rate limits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the tool's purpose and lists the key return fields, followed by cost information. No redundant or filler content.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple hash-lookup tool with one parameter, the description provides the necessary purpose, return fields, and cost. However, it omits any mention of error conditions (e.g., invalid hash, not found) or whether the tool is read-only, which could be useful in a complete context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema fully documents the single 'hash' parameter with type, pattern, and description, so the description adds no additional semantic meaning for parameters. It simply refers to 'transaction hash' in passing, which does not go beyond the schema's coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool returns Base transaction status with specific fields (success/revert, block number, confirmations, gas used, gas price) for a transaction hash. This is specific and unambiguous, though it does not explicitly distinguish itself from sibling tools like base_block_number or base_gas_price beyond the resource type.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use the tool—whenever a Base transaction hash needs status and receipt details—but it does not provide explicit guidance on when not to use it or how it differs from alternative status-checking tools. No exclusions or selection criteria are given.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full behavioral burden. It adds useful context: the specific canonical contract, the cost ($0.003/call via x402), and the return shape (atomic and formatted values). It does not explicitly note read-only behavior or failure modes, but the balance-check nature is strongly implied and the provided details exceed minimal disclosure.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single, dense sentence delivers the core purpose, network, contract, return type, and pricing without redundancy. Every phrase earns its place and key information is front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple single-parameter balance check with no output schema, the description covers the essential operational facts: what is read, from where, what it returns, and what it costs. It could be more complete with explicit read-only clarification, but nothing critical is missing for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage for the single address parameter, so the schema already documents the parameter. The description does not add meaningful semantic detail beyond what the schema provides, warranting the baseline score.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb ('Check'), a precise resource (a Base wallet's USDC balance on the canonical Base USDC contract), and the return format (structured JSON with atomic and formatted values). This clearly identifies what the tool does and distinguishes it from related siblings such as base_usdc_transfer_check and base_wallet_profile.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives no guidance on when to use this tool versus alternatives. It does not mention scenarios, exclusions, or recommend siblings for different needs, leaving the agent to infer the appropriate context from the name alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden. It discloses the internal behavior: 'decodes every USDC Transfer log in the receipt (from, to, amount)' and the binary outcome 'settled true/false'. It also transparently states the cost ($0.004/call). Missing edge cases like what happens for non-USDC or non-existent transactions, but the provided detail is above average.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single well-structured sentence that front-loads the core purpose ('Verify a Base mainnet tx hash'), then elaborates with mechanism, use case, and cost. Every phrase earns its place; no filler or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-parameter tool with no output schema, the description is complete: it explains what the tool checks, how it checks it, what it returns (true/false), when to use it, and the cost. The sibling context shows it's well-positioned among related tools, and the description fully satisfies the need.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already fully describes the single 'tx' parameter with pattern and description, giving 100% coverage. The description adds valuable semantic context by specifying this is a 'Base mainnet tx hash' and that it's specifically for USDC, which is not in the schema. This elevates it above the baseline.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's specific verb and resource: 'Verify a Base mainnet tx hash actually moved USDC'. It goes further by explaining it decodes every USDC Transfer log and answers settled true/false, which sharply distinguishes it from sibling tools like base_tx_status or base_usdc_balance.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context: 'the check an x402 seller runs before trusting a payment reference'. This tells the agent exactly when to use it. However, it doesn't explicitly mention alternatives or when not to use it, such as when a simpler tx status check would suffice.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations exist, so the description must cover behavioral aspects. It states no signup/API key needed and mentions a cost, but does not explicitly say whether it's read-only or non-destructive. It does mention 'bounded transfer activity' which hints at limitations. It adds some value beyond schema but misses safety/behavioral details.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that is efficient and packs key differentiators (no signup, cost, output categories). It is concise but could be reorganized slightly for clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (5 params, no output schema), the description is too sparse. It lists output categories but doesn't explain what 'bounded transfer activity' means, how lookback_blocks affects results, or what the evidence hash is for. The lack of details about parameter behavior and output expectations leaves gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is only 20% (only asset has a description), and the tool description does not explain most parameters. It mentions 'bounded' and 'counterparties' but doesn't map to lookback_blocks or include_counterparties. It fails to clarify the meaning of the address parameter or how chain works. Description adds little beyond schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: profiling a Base wallet, with explicit details about what it returns (balances, transfers, counterparties, freshness, evidence hash). It distinguishes from sibling tools by being a comprehensive profile rather than a specific query (e.g., base_usdc_balance, base_transfer_search).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance on when to use this tool over siblings. It does not mention alternatives or exclusion criteriaate (e.g., when to use base_usdc_balance instead). The description implies a general profiling use case, but no explicit when/when-not guidance is provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the transparency burden and does it well: it discloses isolated ephemeral compute, per-item schema validation, idempotent manifest behavior, the $0.02/call cost, and refundable unused execution on delivery failure. It stops short of explaining failure modes for invalid URLs or schema mismatches.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is one compartmentalized paragraph with two coherent sentences. It fronts the core extraction behavior, then supplies key constraints and costs. No redundant language or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description is largely complete for selection purposes: batch size, public-only URLs, schema validation, isolation, idempotency, cost, and refund behavior are all covered. Lacking an output schema and annotations, it still leaves a few questions around failure modes, but it gives strong enough context for an agent to invoke correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds some semantic meaning to the parameters: 'up to 10 public URLs' maps to items, and 'reconciled idempotent manifest' implies the role of idempotency_key. However, it never directly explains that idempotency_key must be supplied to make retries safe, and with schema coverage at 0%, the description has gaps around the exact structure and semantics of the items array.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: extract JSON from up to 10 public URLs. It adds distinctive scope (isolated ephemeral compute, per-URL JSON Schema validation, reconciled idempotent manifest) that clearly separates it from single-extract or non-validating siblings like extract_json or batch_url_json.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use the tool: for batch JSON extraction from public URLs with schema validation and a paid x402 call. It clearly implies a multi-HTTP-URL batch scenario, but it does not explicitly exclude private URLs or direct users to alternatives like extract_json or batch_url_json.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden and does disclose important behavioral traits: it is a pre-paid operation ($0.02/call via x402), idempotent via a receipt, and limited to 10 jobs. However, it does not describe failure semantics, partial job failures, return format, or authentication requirements, leaving gaps for a paid operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with the core purpose, and includes only essential details (cost, idempotency, batch limit). There is no fluff or repetition of schema field names.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a paid batch operation with no output schema, the description covers the core function and payment but lacks details about what the returned receipt/batch looks like, error handling, or retry behavior. It is adequate for basic selection but not fully complete for safe invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 0% description coverage, so the description must compensate. It adds meaning by explaining that 'jobs' are URL-to-JSON extractions and limits them to 10. It does not explicitly explain 'idempotency_key' beyond the word 'idempotent,' which is a partial gap. Still, the description provides more than the schema alone.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action: 'Run up to 10 bounded HTTPS URL-to-JSON extraction jobs.' It specifies the resource (URL-to-JSON extraction), batch limit, and adds unique traits (prepaid, idempotent receipt, cost) that distinguish it from siblings like web_extract or fetch_x402_content.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for batch extraction of up to 10 URLs and mentions a cost, offering some context. However, it does not explicitly state when to use this tool vs alternatives, nor when not to use it. The batch size and payment model serve as implicit guidance but no clear exclusions or alternatives are named.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Despite having no annotations, the description discloses the exact output contents (categories, counts, calls, payers, share) and the cost ($0.003/call). It does not explicitly confirm a read-only operation, but the 'snapshot' wording suggests a non-mutating query, which is reasonable.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that front-loads the core purpose, then lists the key data points and cost. Every word adds value, and the dash structure makes it easy to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema and no annotations, the description still conveys the essential return value: a classification of the catalogue into categories with multiple metrics. It also includes pricing, making it sufficiently complete for an agent to decide when to invoke it.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, so the description correctly implies no inputs are needed. This baseline of 4 is appropriate since the schema is empty and there is nothing to explain.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description explicitly states the tool provides a snapshot of the latest x402 Bazaar catalogue classified into 9 service categories with specific metrics (listing count, settled 30d calls, unique payers, share). This clearly distinguishes it from other bazaar tools that focus on different aspects, such as new listings or pulse.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase 'Where the x402 Bazaar demand actually is' implies this tool is for understanding demand distribution by category. It gives a clear context for use, though it does not explicitly name alternatives or state when not to use it, which would elevate it to a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the behavioral transparency burden. It adds useful context: x402 payment, exact per-call costs, loopability, and repeat-call telemetry. But it does not disclose pagination mechanics, required authorization flow, failure modes, or whether the operation is purely read-only.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact: two sentences, no filler, with the core purpose front-loaded and pricing in the second sentence. The long metric list is dense but each item conveys a meaningful inclusion.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

This is a multi-mode tool with six parameters and no output schema, but the description omits per-view parameter requirements, how cursor-based looping works, what the response looks like, and what the telemetry/snapshot parameters control. An agent would likely struggle to invoke it correctly without additional documentation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate, but it only hints at 'view' through 'category feed' versus 'scout digest' and at 'cursor' through 'Loopable.' The meanings of categories, max_changes, since_snapshot, and client_polled_at are left entirely to inference, which is insufficient for a six-parameter tool.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description identifies the tool as a Bazaar category heat feed with an optional bundled scout digest, and enumerates the digest contents (heat, deltas, new listings, price changes, pulse, seller rank, telemetry). It is specific about the resource and the two modes, though it lacks an explicit verb like 'return' or 'fetch.' The 'bundled' wording helps differentiate it from the many individual Bazaar sibling tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage contexts via 'Loopable' for repeated polling and 'bundled scout digest' for getting multiple metrics at once, and it gives per-view pricing. However, it does not explicitly say when to use this tool instead of calling bazaar_category_heat, bazaar_delta, bazaar_pulse, or other siblings, nor does it state exclusion criteria.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden. It discloses the diffing behavior, the types of changes reported, and the cost ($0.004/call via x402), which is valuable context. It doesn't cover edge cases like snapshot availability or output format, but for a zero-parameter tool, the core behavior is transparent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The entire description is one well-structured sentence that front-loads the purpose and appends cost information. Every word adds value, with no filler or redundant phrasing.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description explains what the tool does, its scope, and its cost. Given the lack of output schema and annotations, it is reasonably complete for a simple, parameterless diff tool. It could mention output format or snapshot dates, but the core use case is clear.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema is empty (0 parameters), and the description appropriately focuses on output/behavior rather than parameter syntax. The baseline score of 4 applies because no parameter explanation is needed.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool diffs the two latest daily snapshots of the x402 Bazaar catalogue, reporting added, delisted, and price-changed resources with before/after amounts. This specific verb+resource+scope distinguishes it from sibling bazaar tools like bazaar_new_listings or bazaar_price_stats.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for tracking overnight changes but does not explicitly state when to use this tool versus alternatives like bazaar_market_report or bazaar_trending. No exclusions or 'use instead' guidance are provided, leaving the comparison implicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden. It discloses the tool's behavior: performs a live probe of the resource, evaluates specific criteria (valid 402, description, output schema, category, price floor), reviews day-by-day snapshot history (price churn, delisting), and charges $0.01/call. This is significant context beyond a simple 'lint' statement.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core action and quickly explains the scoring mechanism and cost. It is a single sentence with multiple clauses, but every clause adds necessary information about the tool's function and components, so it earns its length.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given a single-parameter schema and no output schema, the description is quite complete. It explains what the tool returns ('0-100 quality score'), what inputs it analyzes, and the cost. It does not detail the exact output format, but for a lint tool this is sufficient. The usage context is also provided.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% coverage for the single parameter 'resource' with a description 'The listed resource URL to lint'. The description adds no new parameter-level detail, but the schema is already sufficient. Baseline 3 applies because the description does not need to compensate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb+resource: 'Lint an x402 Bazaar listing', and clarifies the purpose with 'before buying or before publishing your own'. It clearly distinguishes from sibling tools like bazaar_market_report or bazaar_delta by focusing on a single listing's quality score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states when to use the tool: 'before buying or before publishing your own'. It implies the tool is for pre-transaction validation, but does not name alternatives or exclusions. This is clear context, yet lacks explicit 'when not to use' guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden. It discloses the data source (daily full-catalogue snapshots), the cost ($0.50/call), and what is included. It does not mention rate limits or authentications, but for a read-only report, these are less critical. The cost disclosure is a valuable behavioral trait.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact, front-loaded with the tool's purpose, and every sentence provides value. It lists contents efficiently and adds cost and snapshot timing without fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter tool with no output schema, the description is complete. It tells the agent exactly what to expect (a JSON dossier with named metrics), the data timeliness, and the cost. This is fully sufficient for selecting and invoking the tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, so there is nothing to document. The description adds useful context about the report's content and freshness without needing to explain params. Baseline 4 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool provides 'the full state of the x402 Bazaar in one JSON dossier' and enumerates the included metrics (totals, price distribution, network split, top services/sellers, etc.). This specific verbless statement thoroughly differentiates it from sibling tools that focus on individual aspects.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use it naturally: for a comprehensive market overview. It says it's built from daily full-catalogue snapshots and costs $0.50/call, providing context. However, it does not explicitly name alternatives or state when not to use it, so it falls short of a perfect score.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Since no annotations are provided, the description fully discloses the tool's behavior: it compares daily snapshots to derive new listings, returns specific fields (service, network, price, seller address), and states the cost of $0.003/call via x402. This is comprehensive and transparent for a read-only query tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that is front-loaded with the core purpose, followed by the method and cost. It is concise, with no filler or redundant information, and every phrase adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Even without an output schema or annotations, the description provides enough context to understand the tool's behavior, including the exact selection algorithm and output fields. For a simple tool with no parameters, this is a complete and self-explanatory description.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, so the schema provides no additional meaning. The description compensates by explaining what the tool does and what it returns. According to the baseline for zero parameters, this is a high score.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: identifying resources newly listed on the x402 Bazaar. It specifies the exact resource (x402 Bazaar), the verb (just listed), and the scope (everything in the latest daily snapshot missing from the prior one), which distinguishes it from sibling tools like bazaar_delta or bazaar_category_heat.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description makes the intended use clear by phrasing it as a question ('Which resources just listed...'), indicating it is used to discover new listings. However, it does not explicitly mention when not to use the tool or suggest alternative sibling tools, so it falls short of a perfect score.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden. It adds valuable behavioral context: the data comes from 'the latest daily full-catalogue snapshot' (indicating potential staleness), the cost is disclosed ($0.002/call via x402), and the optional network filter is described. It does not mention output format or error behavior, but given the read-only nature, the key traits are covered.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with the core function, and contains no fluff. It efficiently conveys the stats provided, the snapshot source, the optional filter, and the cost. Every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple tool with one optional parameter and no output schema, the description covers the essential context: what data is returned (percentiles, price bands, medians), the data source (daily snapshot), and cost. It could mention the response structure or error handling, but for a stats query, the description is largely complete. Slightly more detail on return format would push it to a 5.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The only parameter, network, is fully described in the schema with an example and instruction to omit for all networks. The description repeats this via 'Optionally filter to one network.' Since schema coverage is 100%, the description adds no new semantic meaning beyond what the schema already provides. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states what the tool does: it provides a percentile distribution (atomic + USD), USD price bands with market share, and per-network medians for x402 Bazaar listings, based on a daily snapshot. This is a specific, distinct function compared to sibling tools like bazaar_pulse or bazaar_trending, which focus on other aspects. The purpose is immediately clear.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage context—'How x402 Bazaar listings are priced right now'—and mentions the optional network filter, but it does not explicitly state when to use this tool versus alternatives like bazaar_market_report or bazaar_delta. There are no exclusions or alternative tool recommendations, so the guidance is implied rather than explicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses the cost ('$0.002/call via x402') and the data freshness ('latest completed daily snapshot'), which are useful behavioral traits. However, it does not mention return format, error conditions, or any rate limits, leaving some behavioral uncertainty for a zero-parameter tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, well-structured sentence that front-loads the primary purpose and includes critical details (contents, freshness, cost). Every word earns its place with no redundancy or extraneous information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity (zero parameters, no output schema), the description covers the essential aspects: source, contents, frequency, and cost. It does not explain output structure, but that is not necessary when no output schema exists and the tool is a straightforward data snapshot. A perfect score would require distinguishing guidance from sibling tools.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, so the description does not need to explain any. The baseline for 0 params is 4, and the description appropriately focuses on the tool's output rather than input, which is irrelevant here.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the resource ('x402 Bazaar market pulse') and specifies its contents ('catalogue totals, top services by call volume, new listings and networks'). While it lacks an explicit verb like 'get' or 'list', the intent is unambiguous. It distinguishes from siblings by naming 'x402 Bazaar' specifically, though it doesn't differentiate from the similar-sounding 'market_intel'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description does not state when to use this tool versus alternatives. It mentions 'latest completed daily snapshot' implying a use case for fresh data, but there is no explicit guidance on when not to use it or what alternatives exist. With multiple sibling tools offering market data, this gap is noticeable.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden of behavioral disclosure. It reveals that the tool uses the latest daily snapshot, focuses on settled 30d calls, and lists specific data included. It also mentions the call cost ($0.003 via x402), adding useful context beyond what schema or annotations provide. However, it does not explicitly state read-only nature or potential rate limits, but for a simple data query, this is adequate.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, tightly packed with relevant detail: ranking criteria, time window, snapshot source, included fields, and cost. Every phrase earns its place with no redundancy, and the key purpose is front-loaded in the first few words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter query tool, the description is remarkably complete. It explains what data is used (latest daily snapshot), the metric (settled 30d calls), the ranking scope (top 25), and the output components (listings, unique payers, busiest resource). No output schema exists, but the description effectively communicates the return content.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, so there is nothing for the description to clarify. The description instead focuses on what the tool returns, which is more relevant. Per rubric, a baseline of 4 applies when there are no params.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: ranking top 25 x402 Bazaar seller addresses by settled 30d calls. It specifies the exact output content (listings, unique payers, busiest resource) and distinctively differs from sibling bazaar tools like bazaar_market_report or bazaar_pulse, which focus on broader market trends rather than individual seller ranks.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The opening phrase 'Who is actually earning on the x402 Bazaar' gives a clear use case, implying it is for identifying top-earning sellers. It does not explicitly mention alternatives or when not to use it, but the context is clear enough that an agent can infer when this tool is appropriate.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals the data source (daily full-catalogue snapshots), comparison method (day-over-day), output categories, and cost ($0.003/call via x402). This goes beyond a generic description, though it does not explicitly state read-only behavior or output format.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, well-constructed sentence that front-loads the core question and includes all essential details: the resource (Bazaar services), metrics (settled calls, unique payers), time frame (day-over-day), categories (movers, decliners, new entrants), data source, and cost. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter tool with no output schema, the description is reasonably complete: it explains the conceptual output, the cadence of snapshots, and the pricing. It does not detail the exact result structure, but the absence of an output schema makes that less critical. It could also mention that it is read-only, but the context is sufficient.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, so the schema is fully covered. Per the baseline for 0-parameter tools, the description does not need to add parameter details. It could mention that no input is required, but the context signals make this unnecessary.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: identifying which x402 Bazaar services are gaining settled calls and unique payers fastest, with specific categories (day-over-day movers, decliners, and new entrants). This distinguishes it from sibling tools like bazaar_pulse or bazaar_delta by specifying exact metrics and snapshot basis.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for discovering currently trending Bazaar services ('gaining... fastest right now') but does not explicitly state when to use this tool over alternatives or provide exclusions. No sibling tool references are given, leaving some ambiguity for an agent choosing between related bazaar_* tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Without annotations, the description carries full burden for behavioral disclosure. It mentions 'ephemeral' and '$0.02/call,' which add some context, but it does not explain failure behavior, side effects, authentication requirements, or what AEP-1.0 evidence actually contains. The lack of an output schema makes this gap significant for a browser automation tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, compact sentence that includes the core behavior, cost, and evidence format. Every phrase contributes meaning, with no filler or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

This tool has nested parameters, no annotations, and no output schema, yet the description is extremely short. It omits critical details like how the action object should be structured, what AEP-1.0 evidence includes, and how results are returned, making it incomplete for a tool of this complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate for all parameters. It only partially explains 'expected' via 'selector or text assertion.' The action object's types (click/type/goto), the purpose of url, and the role of request_id are entirely unexplained, leaving agents without the needed semantics for invocation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description specifies a clear action: 'Run one ephemeral Playwright browser action and verify a selector or text assertion, returning AEP-1.0 evidence.' This identifies the resource (browser action), the operation (verify), and the output (evidence), effectively differentiating it from siblings like web_extract or batch_url_json.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no explicit guidance on when to use this tool versus alternatives like web_extract or purchase_web_extraction_sample. It implies usage through its description but lacks any when/when-not context or alternative recommendations.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are present, so the description carries the full burden. It adds valuable behavioral guarantees: 'the answer is validated against your label list' ensures a real label is returned, and the pricing ($0.005/call via x402) is an extra non-obvious detail. It does not cover failure modes, but the tool's simple classification behavior makes this less critical.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single well-structured sentence that front-loads the action and packs in the label constraint, use cases, validation guarantee, and pricing. Every phrase earns its place with no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

This is a simple two-parameter tool, and the description plus schema fully specify inputs, output behavior (exactly one label), validation, and cost. No output schema is needed because the labels parameter already states the return characteristic, and the description adds meaningful context for real-world use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%—both parameters are fully described in the schema (text truncation, label constraints, response guarantee). The description's mention of '2-20 labels' and the response being one of them largely repeats schema content, providing no new parameter-specific meaning beyond context.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and resource: 'Classify text into exactly one of your 2-20 labels.' It also names concrete applications (support triage, intent detection, content routing) that immediately distinguish it from sibling tools like sentiment or extract_keywords.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear usage context by listing example applications, and the phrase 'your 2-20 labels' implies it is for custom labels. However, it does not explicitly mention when NOT to use it or name alternative tools, so it lacks explicit exclusions or alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full behavioral disclosure burden. It does add useful behavioral context: the tool returns a brief with citations, business profile, competitor analysis, market signals, and risks, and it costs $0.50/call via x402. However, it does not disclose failure modes, payment/authorization issues, data freshness, or any side effects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single efficient sentence that front-loads the main deliverable and includes the most decision-relevant detail, the cost. It avoids boilerplate and repetition. The 'via x402' phrase is compact but may be unclear to agents unfamiliar with the x402 payment context.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description lists the key output categories, so an agent can form a reasonable expectation of the result. However, it does not explain how filing_type changes the output, what the response structure looks like, or how errors such as unknown tickers or payment failures are handled. There is no output schema to compensate for those gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema documents ticker with an example and filing_type as an enum with a default, but the description adds no parameter-specific meaning. It does not explain how filing_type affects the research brief or whether ticker alone is sufficient. With 50% schema coverage and a self-explanatory enum, the schema carries most of the semantic load.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a concrete deliverable ('Company research brief') and lists its contents: cited sources, business profile, competitors, market signals, and risks. It clearly indicates the tool produces company-focused research, which distinguishes it from broader market-intelligence siblings. It lacks an explicit verb like 'retrieves' or 'generates,' but the noun phrase conveys purpose effectively.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description does not state when to use company_research versus related siblings such as market_intel, answer_with_sources, or web_extract. There are no exclusion criteria, prerequisites, or routing hints. An agent must infer usage solely from the tool name and the output description.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must convey behavioral traits, but it only mentions a per-call cost. It does not disclose whether the tool creates persistent state, requires authentication, has side effects, or what the output format is.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with no filler; the first states the core purpose and the second adds pricing information. It is front-loaded and easily scannable.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite the tool's complexity (7 required params, no output schema, no annotations), the description is minimal and omits critical context such as return value structure, behavioral constraints, and parameter semantics. It is not complete enough for reliable invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has seven required parameters with zero descriptions, and the tool description does not explain any of them. The mention of 'refund rules' loosely relates to refund_capability, but the other six parameters (e.g., product_type, max_latency_ms) are completely unaddressed.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('compile') and resource ('multi-rail merchant payment policy') with a list of rule types, making its function clear. It does not name alternative tools or explicitly differentiate from siblings, but the scope is distinctive.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no information about when to use this tool, what triggers its use, or how it compares to sibling tools like settlement_verify or x402_receipt_lookup. There are no usage conditions or exclusions stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the transparency burden. It adds useful context about live market data, source attribution, and cost, but does not disclose behavior such as error handling, response shape, or whether the price is cached/paginated.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that efficiently packs purpose, data source, attribution, and cost. No wasted words or redundant details.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple one-parameter price lookup, the description covers the essential purpose and adds cost and source attribution. The lack of an output schema is mostly mitigated by stating the price and source, though a brief mention of the response structure would make it complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The symbol parameter is fully documented in the schema with an example. The description only repeats 'one token symbol' and adds no additional semantics about format, case sensitivity, or accepted values.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool provides the current USD price for a single token symbol using live market data. It mentions the specific resource (token price) and scope (one symbol), but does not explicitly contrast with similar siblings like token_metrics or market_intel.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied: use when you need a quick USD price for one token. However, there is no explicit guidance on when to choose this over sibling tools, nor any mention of limitations or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description discloses the tool's side effects: it's a non-mutating echo, requires x402 payment, and costs $0.01/call. It adds meaningful context beyond the schema, though it doesn't detail response format or failure behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with the core action, followed by the diagnostic context and cost. No redundant filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

As a simple diagnostic echo tool, the description covers purpose, cost, and behavioral context sufficiently. It doesn't specify the timestamp format, but that's a minor detail for an echo endpoint.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has zero defined properties but allows arbitrary query parameters with a clear description. The tool's description reinforces that query parameters are returned verbatim, and since parameters are free-form, there is little more to explain.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool echoes request query parameters back with a timestamp, and identifies it as an x402 client diagnostic. This specific verb+resource makes it distinct from the sibling analysis tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It conveys a diagnostic use case ('exercises the payment headers, not just the HTTP client') and mentions cost, implying it's for testing x402 integration. However, it doesn't explicitly state when not to use it or name an alternative, but given the sibling set, the context is sufficient.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description discloses key behaviors: the request is bounded, costs $0.01, and the target body is not returned. However, it does not warn about sending user-supplied headers/body to arbitrary endpoints or discuss side effects, prerequisites, or error handling.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single dense sentence that efficiently conveys the verb, resource, output scope, constraint (no body), and cost. Every clause adds value with no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 5 parameters, no annotations, and no output schema, the description covers the core purpose, return fields, and constraints. It lacks details on assertion validation or method defaults, but the schema partially fills that gap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 60% with descriptions for target_url, headers, and task_assertions, but method and body lack descriptions. The description adds no parameter-specific detail beyond noting the request is bounded and x402-related, leaving some parameters under-explained.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool makes one bounded request to a public HTTP endpoint and reports specific data (status, x402 payment signals, latency, assertion validity). It also explicitly notes the target body is not returned, distinguishing it from siblings like web_extract.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies use for lightweight HTTP endpoint testing with a cost per call, but it does not explicitly state when to choose this tool over alternatives or mention any exclusions. No direct comparison to sibling tools is provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden and does excellently: it discloses parse-validation, automatic retry, and a clean failure mode. It also mentions cost. These behavioral traits go well beyond the schema, which only defines the inputs.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, well-structured sentence that front-loads the main purpose, then adds behavioral details and cost. Every clause earns its place with no wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple two-parameter tool with no output schema, the description adequately covers purpose, behavior, failure modes, and cost. It does not need to explain return values since the output is described as JSON or a clean failure, and the schema param is self-explanatory.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the schema already documents both parameters. The description adds examples of text types but no additional syntax or constraints beyond the schema. The baseline of 3 is appropriate; the description does not meaningfully enhance parameter understanding.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it converts unstructured text into structured JSON using a provided JSON Schema, with specific examples (emails, invoices, listings, bios). This is a specific verb+resource and distinguishes it from siblings like extract_keywords or classify_text.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It provides clear context for when to use the tool (when you have unstructured text and a JSON schema), but it does not explicitly name alternatives or exclusion criteria. The use case is well-defined, but no 'vs alternatives' guidance is given.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It mentions the output format ('clean JSON arrays') and pricing, but omits important behavioral details like the 8,000-character truncation limit, rate limits, or auth requirements. This leaves gaps in transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that front-loads the main action, includes pricing, and uses no filler. Every word contributes to conveying purpose and value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers purpose, output format, use cases, and pricing. The schema covers the parameters. While it doesn't mention the 8,000-character truncation limit, that is available in the schema. The lack of an output schema makes the 'clean JSON arrays' statement somewhat vague, but overall it is adequately complete for a simple extraction tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3. The description adds context about ranked output and entity types (people, orgs, places, products), but it does not specifically explain the parameters beyond what the schema already provides. It enhances understanding of the output, but not the parameters themselves.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool extracts ranked keywords and named entities from text, using a specific verb and resource. It distinguishes itself from sibling tools like classify_text or summarize_text by focusing on extraction and entity recognition.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit use cases ('for tagging, indexing, and enrichment pipelines'), giving clear context for when to use it. However, it does not mention alternatives or exclusions, so it stops short of a full 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden. It discloses automatic payment handling, cost ($0.02/call), free tier limits (1 fetch/day), and that it returns payment proof. This is valuable behavioral information beyond the input schema, though it doesn't cover failure modes or what happens if payment fails.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise: two sentences that front-load the main purpose and include cost/free tier info. Every word earns its place, with no redundancy or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with no output schema and moderate complexity (payment handling, multiple formats), the description provides enough context: purpose, cost, free tier, return content. It doesn't explain error cases or detailed usage, but it's sufficient for an agent to decide when to call it and what to expect.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already describes all three parameters with reasonable detail (URL must be https, format enum, selector note). The description adds context about output being 'clean article content' and mentions 'content only' for the free tier, but doesn't deeply elaborate on parameter meanings. With 67% schema coverage, a baseline of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb 'Fetch and extract' with a clear resource ('x402-protected web pages') and scope ('handling edge payment automatically'). It distinguishes itself from generic tools like web_extract by focusing on x402-protected content and automatic payment.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description clearly implies when to use this tool: for x402-protected pages where edge payment is needed. It doesn't explicitly name alternatives or exclusions, but the automatic payment handling is a strong contextual indicator that sets it apart from ordinary fetch tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must carry the full burden. It mentions the cost ($0.01/call) but does not state whether the tool is read-only, what it returns, or any side effects. The term 'audit' implies analysis, but the agent cannot infer if it mutates state or requires specific permissions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that captures the core purpose and pricing. It is front-loaded with the action and resource, with no wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 6 parameters, 2 required, nested objects, and no output schema, the description is insufficient. It does not explain what the audit returns, how to specify alternatives, or any constraints. The agent would struggle to use it correctly without additional information.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description must explain parameters. It only hints at two modes ('signed or explicitly declared') which correspond to signed_selected_offer and selected_offer_declared, but does not explain their relationship or the role of max_price_atomic or signature_secret. The agent cannot infer how to construct the required inputs.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: auditing a selected offer against alternatives and quantifying savings. It specifies the two modes ('signed or explicitly declared') and mentions pricing, which is specific and distinguishes it from siblings like agent_readiness_audit.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool over alternatives. The description does not mention any conditions, prerequisites, or reference sibling tools. The agent cannot determine when this tool is appropriate versus other audit or marketplace tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It reveals the source (public records, implying read-only), and mentions cost and payment mechanism ('$0.01/call via x402'). However, it does not disclose the default behavior for ambiguous matches (rejection unless candidates=true is set) or describe error/failure modes, which are critical for a lookup tool. The description adds some value over the schema but leaves significant behavioral gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, well-structured sentence that front-loads the action and resource. It includes the cost as a separate clause, which is useful but not strictly necessary. There is minimal wasted text, and the key information (what, how, cost) is efficiently conveyed. A slight improvement would be to place the cost information at the end, which it is, so the structure is effective.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with six optional parameters and no output schema, the description covers the core lookup action and cost but omits important usage details: that at least one parameter is required (though minProperties in schema conveys this), how parameters interact, and what the ranked candidates and evidence actually look like. Without annotations, more context about fallback behavior or error handling would be expected. It is adequate but not comprehensive.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so all six parameters are documented in the schema. The description lists the query fields but does not add syntax, formatting, or combination rules beyond what the schema provides. It does not, for example, clarify whether parameters can be combined or which combinations are valid. The baseline of 3 applies since the schema already explains the parameters well.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific action ('Resolve a legal entity'), the resource ('public GLEIF records'), and the query criteria (LEI, legal name, jurisdiction, registration ID or country). It also specifies the output ('ranked candidates and evidence'), which clearly differentiates it from general web or company research tools. This is a precise, unambiguous purpose statement.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description does not explicitly mention when to use this tool versus alternatives or any exclusions. While the GLEIF focus implies a use case for official legal entity resolution, there is no guidance on when not to use it (e.g., for non-legal-entity lookups or when richer company data is needed). Given the large sibling list, explicit routing advice would improve clarity, but the purpose is narrow enough to be inferred.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations exist, so the description carries the full burden. It does disclose a meaningful behavioral trait — the $0.01 per-call charge and the payment schemes (Base/Solana exact, or the Base 'upto' authorization) — which is genuinely useful. However, it omits other behavior such as response shape on success/failure and any rate-limits or auth requirements.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two tight sentences that front-load the purpose before the pricing addendum. No filler, but the pricing detail might have been better as an annotation or a trailing footnote; still, every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given there is no output schema, no annotations, and a called-for service that charges money, the description is adequate but leaves gaps: no guidance on expected input format of the message array, no mention of what the caller receives back, and no note on failures. At three parameters and no annotations, it could do more.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% and all three parameters (model, stream, messages) are already documented in the schema, so the baseline is 3. The description adds no parameter-level detail beyond the schema, and notably fails to explain what the 'messages' array items should contain.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific action ('OpenAI-compatible chat completion') tied to a clear resource (the OpenRouter model gateway), pointing to the catalogue endpoint for model discovery. None of the sibling tools is another chat-completion tool, so it clearly distinguishes itself in the toolset.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description contains no guidance on when to use this tool versus alternatives, no context on what kind of requests suit it, and no exclusions. The pricing note is transactional, not usage-directional.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the transparency burden. It discloses a specific behavioral trait—cost ($0.01/call via x402)—and implies a read-only analytical function, but does not explicitly state whether it writes, requires authentication, or describe failure behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loads the core purpose, and includes all essential information without redundancy. Every clause adds value, from the action to the cost model.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of an output schema, the description does a good job of outlining what the tool returns (persistence, price changes, duplicate variants, buy signal). It is complete for a single-listing analysis tool, though it could clarify matching behavior when both name and URL are provided.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage for both parameters (listing_name and listing_url), so the schema already provides the meaning. The description adds no additional parameter-level detail beyond the schema, earning a baseline score of 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb 'Triage' with a clear resource ('one Bazaar listing') and enumerates distinct outputs (persistence, price changes, duplicate variants, buy signal). This clearly distinguishes it from sibling tools such as bazaar_pulse or market_intel.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description clearly states the tool is for triaging a single listing against its snapshot history, implying usage when a user needs a historical assessment of one listing. It does not explicitly name alternatives or exclusions, but the context is clear enough.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description must carry the behavioral burden. It adds cost ('$0.10/call via x402') and source context ('DefiLlama', 'bounded public web context'), but does not explain side effects, data freshness, output shape, failure modes, or what 'bounded public web context' actually means operationally.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single concise sentence with no filler, and it leads with the core purpose. However, vague phrasing like 'bounded public web context' reduces clarity, and the brevity sacrifices needed explanation.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with four optional parameters, no output schema, and no annotations, this description is far too thin. An agent has no idea what inputs to supply, what the result looks like, or how to validate whether the call succeeded.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% and the description does not mention any of the four parameters (chain, symbol, project, token_address). An agent cannot determine how to populate these fields, which are required, or how they interact.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific resource ('DefiLlama market metrics') and an action ('compose'), but 'compose' is ambiguous and does not clearly distinguish this from sibling tools like token_metrics or crypto_price. It communicates the general domain but leaves the exact operation unclear.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to choose this tool over alternatives. The description does not mention use cases, exclusions, or how it relates to similar market-data tools among the siblings, so an agent receives no routing help.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden. It adds useful behavioral context: the call costs $0.005 via x402 and refusals produce deterministic evidence. It does not, however, explain what a successful admission returns or whether any downstream side effect occurs.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single, information-dense sentence front-loads the core purpose and constraints, then appends the essential cost detail. Every phrase earns its place; there is no redundant filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description gives enough to understand the tool's selection constraints and cost, but the absence of an output schema leaves the admission/refusal return contract unexplained. It also does not clarify what 'admit' produces operationally or how the refusal evidence should be consumed by the agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 50%, but the description maps all four parameters to their constraint roles: task relevance, price, Tempo rail, and freshness. It adds meaning beyond the bare enum and field names, yet it does not elaborate on the freshness object structure or how constraints interact.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb ('Admit'), a specific resource ('live MPP public catalog'), and the constraints used (task relevance, price, Tempo rail, freshness). It conveys the gating nature clearly, but it does not explicitly distinguish itself from closely related siblings like mpp_route or oblique_gateway.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance on when to use this tool versus the many routing and gateway siblings. The description implies a catalog-admission context, but it never states when an agent should select this over mpp_route, oblique_gateway, or route_task.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full transparency burden. It discloses the free/paid behavior, output contents (prices, payment methods, MCP schemas, health metadata), and cost ($0.01/call via MPP or x402). However, it does not mention potential side effects, error conditions, or rate limits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, two sentences, and packs essential information (free vs. paid, output details, cost) without redundancy or fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description explains the main behavior and output features but lacks a full picture: no return schema, no explicit usage context, and no mention of edge cases or prerequisites. Given the tool's relative simplicity, it is partially complete but leaves gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Only the 'task' parameter has a schema description; the rest are undefined. The description provides minimal indirect hints (e.g., price_cap relates to 'prices', preferred_chain may relate to 'MPP-native' or 'x402'), but it does not explicitly explain the meaning or expected input format for parameters like constraints, output_format, or preferred_chain.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'MPP-native catalog task-first routing' with explicit differentiation between free (one recommendation) and paid (top three with details) results. It also mentions pricing, making the core function unmistakable.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains the free vs. paid behavior and output differences, but does not explicitly state when to choose this tool over alternatives (e.g., other routing tools). It lacks direct guidance on conditions like 'use when you need pricing or multiple options'.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It does disclose concrete behavioral attributes: a 10% margin receipt, capped float, upstream payment reference, delivery, and an explicit x402 price of $0.001187/call. It does not describe side effects or return format, but it is notably transparent about the transactional nature of the call.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and contains no filler, fitting in two sentences. However, the first sentence is a dense comma-separated list of abstract terms that is grammatically awkward and requires parsing to understand, so it is concise but not optimally structured for quick comprehension.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a single-parameter interface, the description covers the core call context: seller selection, cost, payment method, margin receipt, and delivery. However, with no output schema and no example task or expected return format, an agent must make some assumptions about what the gateway actually returns after invoking a seller.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The only parameter, `task`, has 100% schema description coverage stating it selects an allowlisted observer-proven seller. The tool description itself adds no additional parameter-level detail, so the schema already carries the semantic load; this matches the baseline for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description identifies the tool as an 'Observer-backed gateway over five allowlisted proven sellers' and mentions task-based seller selection, which gives a helpful scope. However, it lacks a clear verb and explicit outcome (e.g., 'routes', 'selects', or 'delivers'), so the exact purpose remains somewhat inferred rather than stated.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives context about the seller pool, pricing, and payment mechanism, but it never states when to use this tool versus alternatives. With siblings like route_task, mpp_route, agentcore_route, and fetch_x402_content, no exclusionary or comparative guidance is provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden and does disclose meaningful behavior: it normalizes inputs, does not hallucinate missing employment or location data, and it exposes the $0.28/call cost. This goes beyond the schema and gives the agent useful expectations about output and side effects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence that clearly names the purpose, includes a key limitation, and mentions cost. Every component adds information; there is no filler or schema repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description gives a clear high-level contract and signal that results are PDL-shaped, but given 7 optional parameters and no output schema, it does not clarify how many signals are needed or what happens if input coverage is insufficient. An agent might reasonably ask whether calling with a single field or an empty payload is valid.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% coverage, with each of the 7 parameters already having a simple description. The description's "person identity signals" phrase adds framing but does not explain parameter combinations, precedence, or minimum requirements beyond what the schema already provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb, "Normalize supplied person identity signals into a PDL-shaped enrichment record," which clearly states the resource, action, and expected output. It also explicitly contrasts with data invention by saying it does not fabricate unavailable employment or location data, making the tool's scope distinguishable and actionable.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

A usage context is implied from the phrase "supplied person identity signals" — the tool should be used when the caller has person identity data and needs a normalized enrichment record. However, it gives no explicit guidance about when not to use this tool or how it compares to alternatives among a very large sibling list.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden of behavioral disclosure. It discloses cost ($0.01/call via x402), boundedness, and that it targets one HTTPS page. However, it omits details about the output format, idempotency behavior, and failure modes, which are critical for a paid operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two short sentences, front-loaded with the core action and pricing. Every word contributes meaning, and there is no redundancy or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema or annotations, so the description must explain what the agent receives and any usage context. It fails to describe the return value (e.g., the extracted content structure), how the idempotency key works, or the exact limits of the 'bounded' sample. This is a significant gap for a paid tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is only 50% (url has a description, idempotency_key does not). The tool description does not clarify the purpose of idempotency_key and merely restates the URL requirement already present in the schema, adding no new parameter semantics.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('buy') and the resource ('a bounded machine-readable extraction sample from one HTTPS webpage'). It also includes the cost and protocol, which helps differentiate it from free extraction tools, though it does not explicitly name alternatives.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives like web_extract or fetch_x402_content. The description implies it is for inexpensive sample extraction but does not state prerequisites, exclusions, or scenarios where other tools are preferred.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description does disclose meaningful behavioral context for a tool with no annotations: it is a paid call ('$0.05/call via x402') and produces cited, structured JSON output. However, it does not explain how the question parameter shapes the synthesis, how multiple URLs are processed, or what happens on failure or duplicate idempotency_key submissions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two tight sentences, action first, no filler. The cost is separated cleanly as its own factual statement, and every word contributes to the tool's purpose or its commercial constraint.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a paid tool with no annotations, no output schema, and three required parameters, the description is too thin. It omits the role of question, idempotency semantics, output structure beyond 'JSON findings', and when to choose this over closely related siblings.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate for the three required parameters. It only hints at urls through 'supplied web pages'; question and idempotency_key are entirely unexplained, leaving an agent without enough meaning to invoke the tool correctly.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a clear verb phrase ('extract and synthesize'), a specific resource ('supplied web pages'), and a concrete output ('cited decision packet with structured JSON findings'). The decision-packet framing helps distinguish it from raw extractors like web_extract or batch_url_json, though it does not explicitly name a sibling.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool versus alternatives such as answer_with_sources, web_extract, or purchase_web_extraction_sample. The phrase 'decision packet' implies a use case, but there is no when-to-use or when-not-to-use guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals that this is a purchase (financial mutation) via x402 and the cost, but it does not describe side effects, required authentication, reversibility, or what the returned token grants. The phrase 'prepaid HTTP-data access token' hints at future use, but critical behavioral details are missing.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core purpose and pricing. It is concise and free of fluff, though it may be too brief to cover necessary context—still, it earns full marks for conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complex nested input schema (method, headers, queryParams) and no output schema, the description is insufficient. It does not instruct the agent on how to construct the request, what the response will look like, or any call expectations beyond the price. An agent would struggle to assemble a correct call without deep schema inspection.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool description adds no explanation of parameters. The schema already documents the nested 'input' object with constraints, and the amount property has a helpful inline description. However, with 0% schema description coverage at the top level and a complex nested structure, the description should at least summarize the required fields and format, which it does not.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action (purchase) and the resource (prepaid HTTP-data access token), and mentions the Apify-compatible shape and pricing. This is specific and unambiguous, but it does not contrast with sibling tools like rep_cheaptokens_buy or purchase_web_extraction_sample, so it lacks differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives no guidance on when to use this tool versus alternatives. It mentions '$1.00/call via x402' but does not state prerequisites, exclusions, or contexts where another tool would be preferred. The agent is left to infer usage from the schema and tool name.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full behavioral burden. It does add meaningful context beyond the schema: the operation costs $0.01, it is paid via x402, and it is a single capped completion. It does not disclose failure modes (payment rejection, endpoint errors), whether refunds occur, or what the response structure will be, which are notable for a paid operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two tight sentences with the verb and resource in the first sentence and the decisive price detail in the second. Every sentence earns its place. The 'priced below the Cheapest Tokens AI winner' claim consumes clarity for a marketing-style comparison and could be dropped, but overall the structure is efficient and front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple 2-parameter paid tool, the description conveys the essential calling context: the kind of completion, the boundedness, the price, and the payment rail. But there is no mention of what the tool returns (no output schema exists), no alternative-selection guidance, and no error/edge behavior, so an agent is only minimally equipped to handle unexpected outcomes.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. 'OpenAI-compatible' implies the `messages` array should follow the OpenAI chat message format (role/content), and 'bounded' aligns with `max_tokens` max 600. But it does not document the exact message shape, defaults, or behavior when `max_tokens` is omitted, leaving room for malformed calls.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: 'Get one bounded OpenAI-compatible ZenMux chat completion'. The qualifiers (bounded, OpenAI-compatible, ZenMux, x402, priced below) differentiate it from siblings like `inference` and the x402 verification tools. The reference to 'the CheapTokens AI winner' is jargon that obscures rather than clarifies, so it stops short of a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage context is implied via the price signal ($0.01/call) and the word 'bounded' — an agent can infer this is for cheap, capped completions. However, no sibling is named and no conditions are given for when to prefer this over `inference` or the other inference/route tools, leaving selection partially to guesswork.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the disclosure burden and does disclose several actionable behaviors: the data source is bounded, unavailable LinkedIn fields are explicitly null, and each call costs $0.30 via x402. It does not mention pagination, result envelope, or empty-result behavior, but the cost and null-field disclosures are especially valuable for an agent deciding whether to call.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single dense sentence contains no filler; each clause adds a distinct fact: the action, result shape, data source, null-field behavior, and per-call cost. It is front-loaded with the verb and resource, making it easy for an agent to absorb quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is moderately complex: 13 parameters, no output schema, no annotations. The description covers source, cost, and output nullity, but omits pagination behavior, result fields beyond 'LinkedIn shape', and any guidance on how to construct a search among the many filters. An agent would likely need a test call or external doc to use it confidently.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description adds no parameter-level context, only the general point about null LinkedIn fields. Several parameter names are self-explanatory (firstName, currentCompany, school), but others like geoId, industryId, and requestContext remain unexplained. With 13 optional parameters and no guidance on combinations or required filters, the description does not compensate for the schema's lack of detail.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description states a precise verb ('Search profiles') and a clear resource ('Linked Panda LinkedIn shape' over 'bounded public Wikimedia data'), which distinguishes it from generic profile-search siblings like rep_stableenrich_search. The mention that unavailable LinkedIn fields are null further defines the output shape. Despite the specialized 'Linked Panda' label, the core purpose is unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies the use case: profile searches that want LinkedIn-shaped results from Wikimedia-derived data, tolerating null fields. However, it does not explicitly state when not to use it, compare with rep_stableenrich_search or pdl_people_enrich, or provide filter-selection guidance. The context is implied rather than spelled out.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

There are no annotations, so the description carries the burden of behavioral disclosure. It usefully discloses normalization behavior, the return envelope, and the $0.28/call x402 payment mechanism. However, it does not state what happens on no match, whether this is strictly read-only, or whether any identity signal is required before calling.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two compact sentences with no filler. The core purpose is front-loaded, and the pricing/payment detail is appended efficiently. Every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description does explain the main return shape: requested enrichment fields plus confidence, freshness, retrieval time, and evidence hash. But for a 7-parameter enrichment tool it omits necessary usage guidance, the need for an identity signal, and no-match behavior, and it does not address sibling alternatives. It is minimally viable for invoking the tool correctly, but there are clear gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is high at 86%, so the baseline is 3; the description adds some meaning by framing the input fields as 'identity signals' and by clarifying that requested_fields controls which enrichment values are returned. It does not mention that at least one identity signal is likely needed, and the required requested_fields parameter has no schema description, leaving room for an invalid call with only requested_fields supplied.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with 'Accountless people-enrichment lookup' and clearly states the operation: normalize identity signals and return requested enrichment fields with confidence, freshness, retrieval time, and evidence hash. It identifies both the resource and the action. It does not explicitly name sibling tools like pdl_people_enrich or rep_stableenrich_search, but 'accountless' and the stableenrich naming help differentiate it.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives no explicit guidance about when to choose this tool over alternatives such as pdl_people_enrich or rep_stableenrich_search. The 'Accountless' label and x402 payment hint at context, but the agent must infer routing rather than being told. No exclusions, preconditions, or alternative tool references are provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the burden. It discloses that private contact and employment fields are null, and mentions cost per call, which is useful. However, it does not explain behavior like pagination, filtering semantics, or what happens with unmatched queries, leaving significant gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, two sentences, with the core purpose front-loaded and additional context (data source, null fields, cost) placed after. It avoids fluff, though 'FullEnrich filter shape' is jargon that might not be universally understood.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 13 parameters, no output schema, and no annotations, the description is insufficient for reliable invocation. It does not cover filter shapes, pagination (offset, search_after), or response format, leaving the agent to guess. Only the data source and cost are contextualized.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It does not explain any of the 13 parameters or the 'FullEnrich filter shape' beyond the name. The agent has no additional meaning about how to construct filters like person_names or current_company_domains from the description alone.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a clear verb ('Search') and resource ('people'), and specifies the data source (bounded public Wikimedia) and that private fields are null. It differentiates from sibling enrich tools by indicating it is a search operation, though it does not explicitly name a sibling.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no explicit guidance on when to use this tool versus alternatives. It mentions 'bounded public Wikimedia data', implying it is not for private data, but does not name other tools or state when not to use it. The agent is left to infer usage context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden of behavioral disclosure. It adds helpful details: the search is bounded, uses public Wikimedia results, and costs $0.01/call via x402. Yet it omits important behaviors such as read-only safety, rate limiting, failure modes, or return format, which an agent may need to handle edge cases.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single dense sentence that front-loads the core action and data source, then adds the exclusion and cost. Every phrase adds value, and there is no filler, tautology, or unnecessary restructuring.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a straightforward search tool with a small schema and no output schema, this description provides essential context: what is searched (Wikimedia), how results are bounded, and what it costs. It does not describe the response shape, which is a minor gap for a search tool, but the schema already covers parameter ranges and the core usage context is sufficient.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description does not explain the semantics of query, limit, or offset beyond the type/default/range information already present in the schema. The word 'bounded' hints at pagination but is not explicitly tied to limit and offset, so the description fails to compensate for the absent parameter documentation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb and noun: 'Run a bounded web search' and identifies the backend resource 'public Wikimedia results'. It also explicitly disclaims being an Exa or stableenrich.dev proxy, which distinguishes it from sibling search tools without needing to inspect schemas.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear context by describing the tool as a bounded Wikimedia-backed search and stating what it is not ('not an Exa or stableenrich.dev proxy'). However, it does not name sibling tools or explicitly state when to prefer this over alternatives like tweets_search or web_extract, leaving the decision rule implied rather than explicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description takes on the full burden of disclosing behavior. It adds useful details: deterministic output and cost ($0.005/call). It does not mention output format or error handling, but for a simple tool this is sufficient.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence that states the purpose, gives examples, and notes cost and determinism without any waste.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (2 params, full schema coverage, no output schema), the description provides a complete picture: what it does, examples, and key behavioral traits. It could mention return value explicitly, but that is implied by 'rewrite'.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already documents both parameters with descriptions (100% coverage), and the description enriches understanding by providing concrete instruction examples and the range of transformations (tone, formality, length, reading level), adding value beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function with a specific verb ('Rewrite text') and defines the scope ('to match an instruction'), including examples of transformations. It distinguishes itself from sibling tools like summarize_text and classify_text by focusing on rewriting rather than summarization or classification.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when to use the tool: whenever text needs rewriting to match an instruction. However, it does not explicitly mention alternatives or exclusions, but the examples imply specific use cases, so it meets the 'clear context, no exclusions' level.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are present, so the description carries the behavioral burden. It explicitly discloses read-only operation, the $0.01/call x402 cost, the 3-query/day free tier, and the free-vs-paid top-1/top-3 result difference. It omits failure modes and exact handoff/evidence behavior, but safety and pricing are covered.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is just two sentences, both contributing useful information (scope + payment/result tiers). However, the first sentence is dense and jargon-heavy, making it harder to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has nested parameters, zero schema property descriptions, and no output schema, yet the description never defines the output shape, the meaning of 'qualified handoff sessions', or how paid mode is selected. An agent gets enough to know what the tool does, but not enough to predict the exact call/response contract.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description must explain the parameters; it only loosely hints that `task` can be a protocol, market-activity, or paid-service discovery query. It gives no semantics for `constraints` (chain, category, max_price) or `seller_delivery_receipt`, so an agent cannot confidently construct these fields.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a concrete action — 'Route ... tasks' — and points at a specific resource ('Agent Economy read-only MCP data'), while also stating free/paid result behavior. It lacks sibling differentiation and leaves jargon ('qualified handoff sessions') unexplained, but the core purpose is identifiable.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description conveys when to use the tool: for protocol, market-activity, and paid-service discovery tasks, with a free-tier caveat. It does not explicitly contrast route_task with sibling routing tools like agentcore_route or mpp_route, nor state when not to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the burden. It discloses 'honest availability semantics' and 'bounded' search behavior, which adds useful context. However, it does not explicitly state read-only status, error handling, or mutation behavior, leaving gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence, front-loaded with the core action and including cost and a behavioral note. It is concise and efficient, though minimal for a tool with six parameters.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with six parameters, 0% schema coverage, no output schema, and no annotations, the description is severely incomplete. It does not explain required parameters, input formats, or response structure, leaving an agent without enough information to invoke it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description provides no parameter-level information. It does not clarify origin_airports, destination_airports, dates, cabin, or passengers, failing to compensate for the lack of schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states a specific verb ('Submit') and resource ('bounded award-flight search') with a Seats.aero-compatible shape. It distinguishes itself from the long sibling list by being the only flight-search tool, making its purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies use for award-flight searches but does not provide explicit when-to-use vs alternatives or any exclusion criteria. Since no sibling is flight-related, the context is implicitly clear but not formally stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The annotation is absent, so the description carries the burden of disclosure. It does disclose a paid API cost ($0.05/call via x402), which is useful. However, it does not disclose the output format (e.g., score vs label), read-only nature, or behavior when both parameters are provided, leaving important gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, concise sentence that front-loads the core functionality and includes essential cost information. Every word adds value, with no redundant or unnecessary content.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the absence of annotations and output schema, the description should explain the return value and clarify the parameter relationship (one-of). It fails to do so, leaving the agent without critical information about what to expect from the tool. The pricing disclosure is helpful but insufficient for completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already provides descriptions for both 'text' and 'topic' (100% coverage). The description essentially paraphrases these ('supplied block of text' vs 'current coverage of a named topic') without adding new meaning, meeting the baseline but not enriching it.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool performs sentiment analysis on either a supplied text block or a named topic. This is specific and distinguishes it from all sibling tools, which do not explicitly cover sentiment analysis.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no explicit guidance on when to choose this tool over alternatives, nor does it specify constraints like 'provide either text or topic, not both'. It merely implies usage by defining the two input modes, but does not contrast with sibling tools or mention exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden. It discloses the key behavioral trait: 'returned only after settlement,' and notes the cost per call ($0.01/call). This is valuable context beyond the basic output description, though it does not cover potential failure modes or exact response structure.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two concise sentences: the first states the output and the payment gate, the second adds the cost and use-case context. It is front-loaded and every phrase earns its place with no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple parameterless tool, the description covers the output format (ISO 8601 + Unix epoch), the settlement requirement, and the cost. Since no output schema exists, a more explicit response structure would improve completeness, but it is already functional for an agent to invoke the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool takes zero parameters, so the schema is fully self-explanatory. The description adds no parameter details, but none are needed. Baseline 4 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it returns the current server time as ISO 8601 and Unix epoch, specifying the exact data provided. This is a distinct, specific resource unlike any sibling tool, so it fully clarifies the tool's purpose.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description frames this as 'the smallest end-to-end probe of the x402 payment path,' giving clear context for when to use it (testing payment integration). It does not explicitly name alternatives, but the sibling list contains no similar tool, so the guidance is sufficient.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden. It discloses several behavioral traits: performs a real on-chain lookup, decodes specific USDC Transfer event fields, returns a verification_id for later re-fetch, and costs $0.01 via x402. It does not detail edge cases like invalid tx_hash or network failures, but covers core behavior well.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with the main purpose. The first sentence efficiently lists key features in a compact list, and the second states pricing. No redundant text.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite lacking an output schema, it enumerates the expected return data (receipt lookup, decoded events, status, confirmations, verification_id). It also notes cost. Given the modest parameter set, the description is sufficiently complete for an agent to decide and invoke.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema already describes both parameters (tx_hash format and chain_id default/limitation) with 100% coverage. The description adds context about the purpose (verifying x402 settlement) but does not add new parameter-level details beyond what the schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Begins with a specific verb+resource: 'Verify an x402 settlement actually landed on Base mainnet.' It clearly distinguishes itself from sibling tools by enumerating unique capabilities: real JSON-RPC receipt lookup, decoded USDC Transfer events, success/reverted status, confirmation count, and stored verification_id.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides clear context: it is for verifying an x402 settlement on Base mainnet after the fact. The mention of 'real JSON-RPC receipt lookup' implies a more thorough check than simpler status tools, but it does not explicitly name alternatives or state when not to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the burden and does well: it discloses cost per call, payment routes, repeat-call friendliness, and the kind of stateful information returned (whether this wallet has called before). It stops short of explicitly stating there are no side effects, but 'operational context check' strongly implies a read-only operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two compact sentences, front-loaded with the core purpose and contents, then adding pricing and repeat-call guidance. Every clause earns its place; there is no filler or repetition of schema/annotation data.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter operational check with no output schema, the description is largely complete: it explains when to call, what information is returned, how much it costs, and which routes can pay. It does not specify the exact output structure, but the listed contents are sufficient for an agent to understand what it will receive.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

This tool takes zero parameters, so the input schema is empty and there is no parameter semantics to explain. Per the baseline for zero-parameter tools, a 4 is appropriate since the description does not need to compensate for missing schema details.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb ('check') and resource ('operational context') and enumerates concrete contents: current UTC time, latest x402 Bazaar pulse, source evidence, and prior wallet activity. This clearly distinguishes it from similar siblings like server_time and bazaar_pulse by combining those into a single context call.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly states when to use this tool ('meant to be called on every run') and even says repeat calls are welcome. It does not name alternatives or give when-not-to-use guidance, but the timing guidance is clear and actionable.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?