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

With no annotations, the description carries the full burden and discloses the important cost per call ($1.00 USDC) plus a clear list of returned data. It doesn't mention other details like rate limits or side effects, but as a read-only data tool, 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?

Three sentences with front-loaded purpose, a clear output list, and cost. Every sentence provides distinct value without 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 0-param tool with no output schema, the description covers the primary purpose and returned data categories. It doesn't specify the exact structure of 'behavioral signals', but is otherwise complete 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?

Tool has zero parameters, so the baseline is 4. The description adds meaning by explaining what the tool returns, even though no parameter details 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?

Description clearly states the tool 'Provides intelligence on agent wallets interacting with the Valorem x402 ecosystem' and lists specific return data types (wallet addresses, spending patterns, top providers, behavioral signals). This clearly distinguishes it from sibling tools like catalog or builder_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?

Usage context is implied through the description: when you need intelligence on agent wallets in the ecosystem. However, it offers no explicit guidance on when to choose this tool over siblings, nor any exclusions or alternative references.

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 the full transparency burden. It discloses the cost ($0.25 USDC per call), which is a key behavioral trait, and lists what data is returned (acceptance rates, block counts, health status). It does not mention data freshness or rate limits, but the cost and content disclosure 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?

The description is three concise sentences, each earning its place: the first states the core purpose and builders, the second details the metrics, and the third notes the cost. It is front-loaded and free of 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 no-parameter, no-output-schema tool, the description is complete. It tells the agent exactly what data will be returned and informs about the required payment. No additional context is needed for selection or 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 tool has zero parameters, so the schema is empty. According to the rubric, 0 params earns a baseline of 4. The description adds meaningful context about the output without needing to describe 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 specifies the exact resource (builder statistics) and action (returns), names the specific Ethereum block builders (Flashbots, Titan, Beaver, BuilderNet, and Quasar), and lists the metrics (acceptance rates, block counts, health status). This clearly distinguishes it from sibling tools like liquidation_watchlist or agent_intelligence.

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 that the tool should be used when builder statistics are needed, but it does not provide explicit when-to-use guidance or mention alternatives. Since the purpose is narrow and distinct from siblings, the usage context is somewhat acknowledged 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?

With no annotations, the description carries the burden of transparency. It explicitly states the tool is free and requires no payment, and it describes the returned content. It does not mention rate limits or read-only status, but for a simple catalog tool, this is sufficient 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?

The description is two sentences long, front-loaded with the main action, and contains no unnecessary words. It efficiently conveys the purpose and key cost 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?

The tool is simple with no parameters and no output schema. The description covers the purpose, the specific contents of the return value, and the cost structure. This is complete for the tool's low 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?

The tool has zero parameters, so the baseline is 4. The description adds no parameter details because none exist, and the empty schema is adequate. No further 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's function: returning the full Valorem MEV Intelligence service catalog with endpoints, prices, and descriptions. This specific verb+resource combination distinguishes it from the sibling tools, which are individual services rather than an overview.

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 should be used to discover available endpoints and pricing. It clearly provides context for when to use it, though it does not explicitly compare it to alternatives or state when not to use it. The free/no-payment note adds practical 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 burden and discloses important behavioral traits: call limit (last 50), output structure (swap direction, pool address, token pair), and cost ($0.10 USDC per call). It does not mention authentication or rate limits, but the disclosed cost and data details provide significant 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 three sentences, front-loaded with the main action, then provides useful detail and cost. Every sentence earns its place with no fluff 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?

Given no output schema, the description adequately describes what the tool returns and what each hint contains, plus cost and use cases. This is sufficient for an agent to understand the tool's functionality and justify 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 tool has zero parameters, and schema coverage is 100%, so the description does not need to explain parameters. It instead describes the output, which is appropriate given the empty input 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 returns the last 50 decoded MEV-Share hints, with a specific action (returns), resource (hints from Flashbots stream), and detail (last 50). It distinguishes itself from sibling tools by mentioning MEV-Share hints, which no other sibling 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 description provides a clear use case: 'Useful for front-running detection and MEV opportunity scanning.' This gives context for when the tool would be relevant, though it does not explicitly mention when not to use it or name 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 burden. It clearly indicates a read-only operation ('Fetches'), discloses the cost ($0.50 USDC per call), and explains return fields along with the meaning of health factors. It lacks details on authentication or error behavior, but for a simple parameterless fetch, this is adequate 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 two sentences, front-loaded with the primary action, followed by a concise list of return fields and cost. Every word earns its place, with no fluff or repetition of schema 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 tool with no parameters and no output schema, the description covers the essential aspects: what it fetches, the source, the key data fields, the interpretation of risk, and the cost. It is not overly verbose but leaves minor gaps such as network specificity and response format, which are acceptable for a simple data fetch.

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 the description correctly avoids extraneous parameter explanations. The baseline for no parameters is 4, and the description adds value by detailing the output fields, which helps the agent interpret the result.

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 function: 'Fetches Aave V3 near-liquidation positions from Valorem's real-time monitor.' It uses a specific verb ('Fetches'), names the resource ('Aave V3 positions'), and adds a source ('Valorem's real-time monitor'). It also details the returned data (wallet addresses, health factors, etc.), which clearly distinguishes it from sibling tools focused on other data types.

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 monitoring liquidation risks by explaining health factors near 1.0 are risky, but it does not explicitly state when to use this tool versus alternatives. No exclusions or comparisons to sibling tools (e.g., pool_spreads, rpc_health) are provided, leaving the agent to infer applicability.

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 responsibility. It discloses the return data (pool addresses, spread percentages, token pairs, profit windows) and the per-call cost ($0.05 USDC), which is sufficient for a read-only detection tool. It does not describe error handling or rate limits, but these are not critical for this simple use case.

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 short sentences with no fluff. It front-loads the core function, then lists return values and cost, making every sentence earn 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 zero-parameter, read-only tool with no output schema, the description covers the purpose, target networks, and return values. It is complete enough for an agent to decide when to invoke it, though it could optionally mention any time window or rate limit constraints.

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 reflects this (100% coverage). The description does not need to add parameter semantics, so the baseline of 4 applies per the guidelines.

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 with a specific verb ('detects') and resource ('arbitrage spread opportunities'), and adds distinguishing details (125+ pools, Base and Arbitrum L2 networks). This effectively differentiates it from sibling tools like liquidation_watchlist or token_safety.

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 when arbitrage spread detection is needed, and the network scope further clarifies context. However, it does not explicitly mention when not to use it or name alternative tools, so it lacks explicit exclusions but provides clear 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. It discloses a key behavioral trait by noting the cost ($0.01 USDC per call) and states data is real-time. However, it does not mention rate limits, data source freshness, authentication, or error behavior, leaving some important operational context unstated.

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, each providing necessary information: what the tool returns and when it is useful, plus the cost. 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?

The tool is simple (no parameters), and the description enumerates the returned metrics, which largely compensates for the lack of an output schema. However, it could be slightly more complete by specifying how metrics are returned (e.g., per-provider object) or which providers are included, but the current level is adequate for agent 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?

The tool has zero parameters, so the schema is trivially covered. The description adds no parameter-specific meaning, but none is needed. Baseline 4 is appropriate because the empty schema cannot be supplemented further.

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 uses a specific verb ('Returns') with a clear resource ('real-time health metrics for multiple RPC providers') and specifies the exact metrics (latency, success rate, error rate, uptime). This clearly distinguishes it from siblings like rpc_proxy, which likely handles actual RPC calls, and other data 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 provides a clear use case: 'Useful for routing decisions in high-frequency MEV strategies.' This gives context for when to invoke the tool, though it does not explicitly mention when not to use it or name alternative 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 discloses latency (~6 ms), cost ($0.001 USDC per call), and the node provider (Valorem's Reth L1 node), which is useful context. However, it does not disclose whether the proxy is read-only or can broadcast state-changing methods (e.g., eth_sendRawTransaction), nor error handling, rate limits, or authentication. This is a moderate gap for a generic proxy.

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, then adds latency and cost. Every sentence earns its place with no fluff. It is appropriately concise for a tool with a well-defined 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 that this is a generic JSON-RPC proxy and the schema fully documents parameters, the description is relatively complete. It covers what the tool does, performance characteristics, and pricing. However, the lack of any output schema or mention of the standard JSON-RPC response format leaves a small gap. Also, the absence of annotations means the description must fully disclose safety/behavioral aspects, which it only partially does (e.g., no explicit statement about write support). Still, for a proxy, the description is strong.

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%, with each parameter having a clear description. The tool description adds method examples (eth_blockNumber, eth_call) and notes 'Pass [] for methods that take no params', which slightly complements the schema. However, the description does not add novel parameter context beyond what the schema already provides, 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 clearly states a specific action: 'Proxies a JSON-RPC call through Valorem's premium Reth L1 node'. It also specifies the scope ('Supports any standard Ethereum JSON-RPC method'), which distinguishes it from the sibling data-lookup tools (catalog, builder_stats, etc.). The verb 'proxies' + resource 'JSON-RPC call' is precise.

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 use: it is a generic proxy for any standard JSON-RPC method, and the cost implies it is a paid service. However, it does not explicitly state when NOT to use it or mention alternatives. Given the sibling list, this tool is clearly the only raw RPC proxy, but explicit exclusionary guidance is absent.

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 cost ($0.02 USDC per call) and the three classification outputs (taxed, rebasing, reflective), which are behavioral traits beyond a mere read operation. It doesn't explicitly state read-only status, but 'classifies' implies it.

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-loaded with the primary action and resource, and includes only essential information (classification categories and cost). No redundant or vague wording.

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 with a single well-documented parameter. The description covers its purpose and cost, which is sufficient for an agent to select and invoke it. It doesn't describe return format, but no output schema exists and the classification categories are already given in the 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?

Schema coverage is 100% with a detailed description of the `token` parameter, including format and example. The tool description adds no new semantic information about the parameter, so 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 tool's function: 'Classifies an ERC-20 token as taxed, rebasing, or reflective' — a specific verb and resource. It also provides the output categories, which fully distinguishes it from the sibling tools (e.g., catalog, pool_spreads) that have different purposes.

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 by mentioning 'MEV and arb strategies', providing clear context for when to use the tool. It doesn't explicitly list exclusions or alternative tools, but no sibling tool overlaps with this functionality, so the implicit guidance is sufficient.

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