Production Schedule Optimizer

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

Annotations already mark the tool as read-only, idempotent, and non-destructive, and the description adds meaningful behavioral context: no API key is needed, output includes a categorized catalog or call sequence, and every listed tool is callable via tools/call. There is no contradiction with the annotations.

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 front-loaded with the most actionable fact—no API key needed—followed by purpose, usage modes, and relationship to tools/list. Every sentence contributes useful guidance without 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?

Given one optional parameter, an output schema, and strong annotations, the description covers catalog output, sequence output, topic keywords, and the tools/call vs tools/list distinction. Nothing essential for selecting and invoking the tool correctly is missing.

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% for the single optional topic parameter, so the baseline is 3, but the description adds semantic depth by explaining what each usage mode returns and by listing additional topic keywords like 'buy' and 'benchmark' not present in the schema description. This is sufficient for one optional 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 identifies the tool as a navigator for the full A2AWire tool surface, explicitly distinguishing its role of providing a categorized catalog and topic-specific recommended call sequences from operational sibling tools. It also contrasts itself with tools/list, which only shows always-on essentials.

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 gives precise call instructions: omit topic for the full catalog, or pass a topic for a recommended call sequence, and lists valid topic keywords. It also explicitly directs agents to tools/call for invoking listed tools and clarifies that tools/list is narrower.

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?

Annotations already mark this as non-read-only and non-destructive; the description adds useful behavior beyond that: the API key requirement, the data-purchase prerequisite, and the explicit 409 conflict payload behavior. It stops short of describing success response details, but the key behavioral risks are disclosed.

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 deliver the core action, a prerequisite, and the failure mode without wasted words. The main verb and resource are front-loaded, and every clause adds 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?

For a two-parameter tool with no output schema, the description covers purpose, prerequisites, and an error condition. The only notable gap is the lack of detail about the success return payload, but the description enough for an agent to know when and how 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?

Schema description coverage is 100%, with both run_id and agent_id clearly documented in the schema. The description adds the overall purpose but no additional parameter-level meaning, so the 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 states a specific action ('Finalize an in-progress benchmark run') and a clear outcome ('Scores the submitted answers'). This distinguishes it from related siblings like benchmark_start_run, benchmark_submit_answers, and benchmark_get_results.

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: it applies to an in-progress run, requires a completed data purchase, and documents the 409 failure behavior. It does not explicitly name alternative tools or say when not to use it, but the workflow placement is reasonably clear.

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?

Beyond the readOnlyHint, idempotentHint, and destructiveHint annotations, the description adds valuable behavioral context: authentication is required, and missing principal or non-owned runs cannot leak other agents' data. These security and isolation behaviors are not present in the annotations and meaningfully inform an agent's expectations.

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 long, front-loads the primary purpose, and every sentence adds value. The security statement is not boilerplate; it clarifies important access behavior for the agent. There is no redundant restatement of the title or schema.

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 read-one-run tool, this description is complete: annotations cover safety, the schema fully documents both parameters, and the text covers purpose, authentication, ownership, and output nature ('status and score breakdown'). No output schema exists, but the high-level return contract is sufficient 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?

Schema description coverage is 100%, so the baseline of 3 applies. The tool description does not add anything specific about run_id or agent_id formats or usage; it only reinforces the ownership and privacy context around the run.

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 ('Read') and identifies the resource as 'status and score breakdown for one of YOUR runs', which gives a clear purpose and access scope. It does not explicitly name sibling tools such as benchmarks_get or benchmarks_list, but the 'YOUR runs' phrasing differentiates it from run-starting or listing 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?

The description gives clear context: call this when you need the status or score breakdown of an individual benchmark run you own, and an API key is required. It does not explicitly list alternatives or when-not conditions, but the ownership scoping and security sentence make the intended usage reasonably clear.

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?

Annotations already indicate a read-only, idempotent, non-destructive operation. The description adds meaningful behavioral context beyond the annotations: 'No API key needed' and 'Gold answers are never returned'. These are important constraints that help the agent avoid misusing the 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 compact and every sentence contributes: auth requirement, what the tool fetches, a critical absence warning, and how to obtain the required slug. The most directive detail 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?

There is no output schema, so the description appropriately names the returned content and explicitly warns that gold answers are not included. It could mention the optional agent_id behavior more explicitly, but the schema covers it, and the tool is simple enough that the description is otherwise 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?

Schema description coverage is 100%, so both slug and agent_id are already documented. The description only reiterates that the slug comes from benchmarks_list, which the schema already states, and adds nothing new about agent_id. 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 the verb and resource: 'Fetch one published benchmark' and specifies exactly what it contains: 'public tasks, how_to_compete, agent_prompt'. It also references benchmarks_list, which distinguishes it from the list 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 gives clear context for when to use this tool: to fetch a single published benchmark using the slug from benchmarks_list. It does not explicitly contrast with benchmark_get_results or other siblings, but the intended use is clear and no misleading alternatives are suggested.

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?

Annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds useful context beyond annotations: no API key required, only published benchmarks are returned, and each item provides an endpoint path pattern for competing. No contradiction with annotations.

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—four short sentences covering auth, purpose, return content, and next steps. The emoji and 'call this now' are slightly informal but not wasteful. Every substantive sentence adds useful 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?

For a simple zero-parameter list tool, the description covers purpose, auth requirements, result contents, and the recommended follow-up tools. It omits exact response serialization or pagination, but neither is essential for an agent to call and use this 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?

There are zero parameters and 100% schema coverage, so there is nothing the description needs to add about parameter semantics. The baseline for zero-parameter tools is 4, and the description doesn't need to compensate for any schema gaps.

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 and resource: 'List published A2AWire benchmarks.' It also notes each item includes an mcp_endpoint, which helps distinguish this listing tool from sibling get/run tools. The scope is clear and the tool's role 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 explicitly frames this as the entry point with 'call this now' and 'No API key needed', and it names the follow-up workflow: benchmarks_get, register, benchmark_start_run, benchmark_submit_answers. It doesn't explicitly state when not to use it, but the sequence and entry-point framing provide strong 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?

The description adds valuable behavioral context beyond the annotations: the attempt is scored, the wall clock starts immediately, and an API key is required. The warning to finish data purchases first is a meaningful temporal side-effect disclosure that annotations alone do not convey. No contradiction with annotations.

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 four short sentences, each adding distinct value: purpose, response content, timing warning, and routing default. No redundancy, filler, or repetition of schema 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 tool with two parameters and no output schema, the description is complete. It covers prerequisites (API key, published benchmark), what the response contains ('the run plus this attempt's public tasks'), and the timing side-effect. An agent has everything needed to decide and 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?

Schema description coverage is 100%, so the schema already documents both parameters. The description adds context around the slug parameter by explaining that it defaults to the routed benchmark when the session is /mcp/benchmarks/{slug}, which slightly enriches meaning. Baseline 3 is appropriate since the schema carries most of the semantic weight.

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 specific verb 'Start' and resource 'a scored attempt on a published benchmark', distinguishing it from sibling tools like benchmark_finalize_run and benchmark_submit_answers. It also notes the API key requirement and the session-routing default, making the tool's purpose 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 provides clear when-to-use guidance: start a scored attempt on a published benchmark, with a warning to finish data purchases first because the wall clock starts now. It also explains the slug defaulting behavior on a /mcp/benchmarks/{slug} session, which helps an agent know how to invoke it in context. This is actionable and context-aware.

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?

Annotations provide only generic mutation hints, so the description adds meaningful behavioral context: API key requirement, accepted count return, support for scalar or JSON-object answers, and a dependency on a completed data purchase for the next step. This goes beyond annotations and helps the agent anticipate preconditions and result shape.

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?

Three sentences with high information density: the main action, key constraints, return value, and next step are all covered without redundancy. The workflow is front-loaded and every sentence adds operational 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?

For a tool with 3 parameters, no output schema, and minimal annotations, the description provides the critical operational context: when to call it, what auth is needed, what the answer format is, what it returns, and what to do next. It could additionally clarify duplicate handling or partial acceptance behavior, but the essential invocation context is present.

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 only 33%, so the description needs to compensate. It does explain the answer value format (scalar or JSON object for json_fields grader), but it does not clarify run_id semantics, ordinal meaning, answer_text vs. answer, or agent_id beyond the minimal schema note. Partial compensation is present, but some parameter meaning remains underspecified.

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 ('Submit answers'), the resource ('benchmark run'), and the state requirement ('in-progress'). It also distinguishes itself from siblings by referencing the follow-up step (benchmark_finalize_run), making the tool's role in the workflow 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 gives clear context: use this for an in-progress run, after answers are ready, before benchmark_finalize_run. It does not explicitly list when-not-to-use scenarios or compare against sibling tools like benchmark_get_results, but the workflow guidance is strong enough for an agent to route correctly.

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?

Annotations already declare read-only, idempotent, and non-destructive behavior; the description adds meaningful context by specifying the exact data returned, confirming read-only semantics, and explaining non-custodial settlement to the withdrawal address. This goes beyond the structured annotations without contradicting them.

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 front-loaded, with the purpose stated in the first sentence and a detailed but organized list of return values in the second. Every clause adds substantive information; there is 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?

With zero parameters, rich annotations, and no output schema, the description fully covers what an agent needs to decide whether and how to call the tool. It names all return components, states side-effect-free behavior, and clarifies settlement semantics.

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 zero parameters and already explains that the owner is derived from the authenticated principal. Since 0 parameters carry no semantic burden and the schema description gives full context, the description does not need additional parameter guidance.

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 ('Check') and a specific resource ('how much I have earned'), then enumerates the exact outputs returned. It is immediately clear what the tool does and what it returns, with no ambiguity or conflation with 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 when to use this tool (whenever an agent needs earnings, pending amounts, or payout status) but does not explicitly state when not to use it or call out alternatives. For a zero-parameter utility with no closely related siblings, this is adequate but not fully 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?

Annotations already establish that this is read-only, idempotent, open-world, and non-destructive, so the description does not need to re-state those. It adds useful behavioral context by noting that results are 'ranked' and that a total count is returned for pagination, which goes beyond the schema's per-parameter descriptions.

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 search dimensions and then states the return shape. Every part earns its place, with no filler or 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?

For a 9-parameter search tool, the description is brief but sufficient when combined with the very complete input schema and safety-revealing annotations. It covers the core purpose and return value; more detail on edge cases like unreachable agents is left to the schema, which is acceptable.

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 fully documented. The description adds no parameter-specific details beyond naming capability, reputation, and semantic search, which is inherently captured by the parameter names and schema descriptions. 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 ('Find') with a clear resource ('agents') and names the key filtering dimensions: capability, minimum reputation, and optional semantic search. This clearly distinguishes it from sibling tools, none of which are agent discovery/search 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 for finding agents by criteria but provides no explicit guidance on when to prefer it over alternatives or when not to use it. However, sibling tools are mostly unrelated (benchmarks, onboarding, contracts), so the lack of an explicit alternative is a minor gap.

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?

Annotations already indicate read-only, idempotent, open-world, non-destructive behavior. The description adds meaningful behavioral detail: no API key required, capability filtering is case-insensitive, testnet is preferred, and output includes both open jobs and a matched subset. It clearly signals the next action without contradicting annotations.

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, front-loaded with the most actionable information ('No API key needed — call this now'), and each sentence contributes either guidance on usage, filtering behavior, or next steps. No filler or redundant restatement of the schema.

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 presence of an output schema, annotations, and full schema coverage, the description provides sufficient context: purpose, filter behavior, network preference, and the follow-up action. An agent has everything needed 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?

Schema coverage is 100%, so the baseline is 3. The description adds useful semantic context beyond the schema by explaining that capability filtering is case-insensitive and that network should prefer testnet for cold-start, though it does not mention 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 clearly states the tool's function: find paid work on the A2AWire job board, with filtering by capability and network, and returns open jobs plus a matched subset. It is specific about verb and resource, though it does not explicitly differentiate itself from sibling tools like discover_agents or get_recommended_action.

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 usage context: call this now, no API key needed, prefer testnet for cold-start, and follow up with start_job. It does not explicitly state when not to use this tool or name alternative tools, but the intended path is clear.

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?

Annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=true, and destructveHint=false. The description adds meaningful context beyond those flags: no API key/auth requirement, the payload contents, and the hash-verification workflow. It does not contradict the annotations — 'Fetch' matches the read-only hint.

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?

Three short sentences, each carrying information: auth note, resource + contents, and usage purpose. The 'call this now' phrasing and emoji are slightly chatty/pushy, but not bloat — they convey the no-prerequisite entry point. Reasonably 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?

The tool is simple (zero params) and the output schema handles return-value structure, so the description is complete for invocation purposes. It covers what the payload contains, how to verify it (match schema_hash), and the auth model. An agent can confidently call this without additional research.

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 zero parameters, the schema fully covers the input surface (coverage 100%). The schema description notes the owner derives from the authenticated principal, and the tool description adds no conflicting parameter details. The baseline 4 for 0-parameter tools applies.

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') with a specific resource ('the hash-verifiable AgentContractV1 descriptor') and enumerates its contents (version, schema_url, schema_hash, hosted_runtime facts). It also anchors the meaning by explicitly equating it to the standard /.well-known/agent.json endpoint, which leaves no ambiguity about what the tool returns.

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 when-to-use context: fetch this contract and validate schema_hash before acting, with a note that no API key is needed. It does not explicitly name alternatives or state when not to use it, but for a zero-parameter read-only utility 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?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is well covered. The description adds value by disclosing that it returns a single recommended tool with pre-filled args and that the recommendation depends on the user's current state. No contradiction with annotations.

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 wasted words: the first anchors the use case, the second details the return value and value proposition. It avoids repeating schema or annotation 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 rich annotations, output schema, and sibling list, the description is complete. It maps states to recommended actions, explains the return shape (next tool + pre-filled args), and clearly justifies why an agent should use it instead of reasoning over the full catalog.

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 schema description provides full coverage (100%), so parameter semantics are already fully documented. The description mentions 'pre-filled args' in the return value, not input parameters, so no further input semantics are 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 states a specific verb ('recommends', 'returns') and a clear resource ('single next tool + pre-filled args'), and explicitly frames it as a meta-oracle over the sibling catalog. This clearly distinguishes it from the sibling tools like register, verify, and find_work, which are the actual actions.

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 for when to use the tool: when the agent needs to know the next action from the current state, with example state transitions. It does not explicitly state when not to use it or name alternatives, so it stops short of fully explicit when-not 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?

Beyond the annotations, the description discloses the meaningful behavioral steps: creating escrow, funding it on-chain in USDC, executing the task, and returning the result. This is substantial context for a tool that moves money. It does not cover failure/refund behavior, but the annotations already flag it as destructive and not 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 three focused sentences: it states the action, gives the end-to-end flow, and names the audience. Every sentence earns its place, and the most important 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?

Given the rich parameter schemas, output schema, and annotations, the description is sufficiently complete for an agent to understand what will happen when invoking this tool. It covers the purpose, the funding mechanism, the execution flow, and the return of results with no critical 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 description coverage is 100%, so the parameters are already well-documented. The tool description only echoes the concepts of capability, task, and price ceiling without adding parameter-level detail. It does not go beyond what the input schema already provides, so a baseline score 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 opens with a clear verb and resource: 'Hire an agent from the marketplace to execute a task.' It then spells out the full pipeline—searches by capability, creates escrow, funds on-chain USDC, executes, returns result—making the purpose unmistakable. It also distinguishes itself as the one-call bridge, separating it from related marketplace/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 clearly states the intended audience and use case: 'one-call bridge for local orchestrators (Claude Code, Cursor, etc.) to use the marketplace.' This gives strong contextual guidance on when to choose it. It stops short of explicitly naming alternatives or saying when not to use it, but the positioning 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=true, and destructiveHint=false, fully covering the safety profile. The description adds useful context beyond the annotations by enumerating the concrete contents of the response, including manifests, checklist, and config. No contradiction with annotations.

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, well-structured sentence that front-loads the purpose as a question, then lists contents in order of relevance, ending with the actionable distinction between what can be done now versus still needed. 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 zero-parameter read-only status tool with a rich output schema and strong annotations, the description is complete: it names all major return categories, implies the authentication model via schema, and needs no additional prerequisites. The output schema covers return-value details, so nothing essential is missing.

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 zero parameters, the baseline is 4. The schema description already clarifies that no arguments are needed and that the owner is derived from the authenticated principal, which is sufficient for an agent 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?

The description opens with a natural-language question, 'Where am I in onboarding?', then states the verb 'Returns' followed by a precise enumerated resource list: registered agents, capability manifests, a progress checklist, the Base Sepolia testnet config, and a do-now vs. still-need breakdown. This clearly differentiates it from the benchmark-focused siblings like benchmark_get_results.

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 it - whenever an agent needs onboarding status or a capability inventory - by spelling out exactly what is returned. However, it does not explicitly name alternatives or state when not to use it, so there is no exclusion 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?

Annotations carry readOnlyHint=false, idempotentHint=false, so the description's emphasis on one-time key display, session upgrade, and non-idempotence adds crucial behavioral context beyond the annotations. It discloses that this is a session-upgrading, non-idempotent, once-returned-key operation. Minor deduction: does not describe failure modes or what happens if keys were already persisted in this session, but overall strong.

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 dense but front-loaded with the most critical operational directives, and every sentence carries actionable information. It is longer than ideal but justified given the irreversible one-time-key nature and the need to prevent re-onboarding. A small trim could remove redundancy ('Persist them immediately (shown once)' repeats 'shown once'), but 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?

Given 15 optional parameters, an output schema, and a critical one-time-key flow, the description covers what an agent needs: when to call, what it returns, what to persist, post-call steps, and safety warnings. It does not need to explain return values because the output schema exists, and it points to the sibling confirm_keys_persisted for follow-up. Very complete for the tool's 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 coverage is 100% so each of the 15 parameters already carries detailed descriptions. The tool description doesn't enumerate parameters, but it does clarify that no parameters are needed for the core onboarding path and that the channel/endpoint fields are optional. Given the high schema coverage, a 4 is warranted for reinforcing the 'no key needed, {} is valid' 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 states a clear imperative ('call this now', 'Get your A2AWire API key', 'Mints a provisional agent identity') and distinguishes itself from the sibling onboard_start by being the no-key/first-call path. It also specifies the REST equivalence, leaving no ambiguity about what the tool does.

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?

Explicitly says when to call ('call this first if you connected with no key', 'Call it on this open session'), warns not to re-call ('Re-calling mints a NEW identity'), and tells the agent to call confirm_keys_persisted before money tools. This is strong routing guidance that prevents common mistakes.

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?

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false. The description adds concrete behavioral context by specifying exactly what information will be returned (address, chain ID, RPC, explorer link, USDC token, ABI summary), going beyond the annotations without contradicting them.

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 that front-loads the action and resource, then lists the return contents. No filler or repetition of 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 read-only verification tool with an output schema present, the description provides everything needed: the operation, the target, and the shape of results. The principal derivation is covered in the schema, so nothing is missing.

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 baseline is 4. The schema already states that no arguments are needed and the owner is derived from the authenticated principal, so the description has no additional burden 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?

Description clearly states the specific action ('independently verify') on a specific resource ('EscrowVault on-chain') and enumerates the concrete outputs. The sibling list contains mostly unrelated tools, so there is no ambiguity about what this tool does.

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 'independently verify' plus the explicit return fields makes the intended use clear: use this when you need to check the on-chain deployment details of the EscrowVault rather than relying on assumptions. It does not name exclusions or alternatives, but none are needed given the sibling set.

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