x402watch

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

With no annotations, the description fully bears the responsibility. It indicates the tool is free, returns wash-filtered data using the same algorithm as paid endpoints, and lists the report contents. However, it does not explicitly state that it is read-only or non-destructive, but the nature of the tool implies no side effects. Slight gap but still good.

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 relatively long but well-structured, starting with the core purpose and then detailing contents and usage context. It could be slightly more concise, but every sentence adds value. 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?

Given the tool has one optional parameter, an output schema exists (making return values clear), and the description enumerates the dataset components, it provides complete context. The agent can understand what data to expect without ambiguity.

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 one optional parameter with a description stating it 'includes a hint about the paid per-address endpoint.' The tool description expands on this by explaining that when an address is provided, the response includes such a hint. The parameter semantics are fully covered and enhanced.

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 'Get the aggregate wash-report dataset' followed by a detailed list of included data, clearly defining the tool's purpose. It also explicitly distinguishes itself from the paid per-address endpoint, ensuring no confusion 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 explicitly states 'Free tier. No payment required.' and contrasts with the paid POST endpoint, providing clear guidance: use this for aggregate free data, and use the paid endpoint for per-address real-time analysis. This effectively tells the agent when to use which tool.

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 provided, so description carries full burden. Discloses free tier (no payment required) and that returned data is wash-filtered using the same v2.0 algorithm as paid endpoints, which adds trust. Does not mention rate limits or side effects, but as a read-only list tool, this is acceptable.

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?

Four sentences, each adding unique value: action and scope, statistics, usage guidance, and data quality note. No filler, front-loaded with key 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 an output schema exists and no nested objects, the description sufficiently covers the tool's purpose, data scope, and quality. Usage guidance completes the picture for an overview 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?

Input schema has zero parameters, so schema coverage is 100%. Baseline score of 4 applies; description cannot add parameter meaning beyond what 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?

Clearly states it lists all 33 x402 service categories with aggregate stats. Uses specific verb 'list' and resource 'service categories'. Distinguishes from siblings by positioning it as a starting point before drilling into specific services or wallets.

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 advises using this tool to understand the ecosystem before drilling into specific services or wallets, which frames its purpose relative to siblings. Does not list explicit when-not-to-use scenarios or alternative tool names.

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 fully covers behavioral aspects: it returns wash-filtered data using the same v2.0 algorithm as paid endpoints, mentions free tier, and lists the data included. It does not mention rate limits or authentication, but for a read operation these are less critical. Overall, it provides sufficient 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 concise: two sentences that front-load the purpose and data content, then add a usage note and algorithm detail. Every sentence adds value without redundancy. Slightly longer than strictly necessary, but still efficient.

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 output schema exists (context signals), the description complements it by enumerating fields in plain language. The single parameter is well-covered. It sufficiently describes the tool's functionality for an agent to invoke correctly, though a brief note on when to prefer this over x402_search_services could improve 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?

Schema coverage is 100%, so the schema already describes service_id as 'Numeric x402 service id (visible in /services list and detail URLs).' The description adds no new parameter information beyond the schema. Thus it meets the baseline but doesn't enhance 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 'Get the full detail record for one x402 service' and enumerates the data fields. It distinguishes itself from siblings like x402_search_services (which returns a list) and x402_check_wash by specifying its purpose: 'evaluate a single service's traffic composition.'

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 'Use this to evaluate a single service's traffic composition' and notes 'Free tier. No payment required.' While it doesn't list when not to use it, the context implies it's for detailed single-service analysis, not for searching or checking wash. Sibling tools are different, so guidance is clear but not exhaustive.

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 provided, but the description discloses refresh frequency (every 5 min), free tier, and wash-filtering, which are useful behavioral traits. It does not mention rate limits or potential limitations, but overall good 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 purpose, and every detail earns its place 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 zero parameters and an output schema (context signal indicates its presence), the description is complete: it covers purpose, refresh, cost, data quality, and distinguishes it from paid endpoints.

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 no parameters (schema coverage 100%), so the description does not need to add parameter details. It effectively explains what the tool returns, fulfilling the role.

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 'Get the last-24-hour trends snapshot' and enumerates specific metrics, distinguishing it from sibling tools like x402_search_services or x402_get_categories.

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 notes 'Free tier. No payment required' and 'Returns wash-filtered data using the same v2.0 algorithm as the paid endpoints,' providing context on when to use this free alternative, though it lacks explicit when-not or alternative 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 provided, so description bears full burden. It discloses pagination, return content (stats, label mix), free usage, and wash-filtered data algorithm. Missing rate limits or authorization details, but sufficient for core 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?

Three sentences, no waste. First sentence defines purpose, second guides usage, third adds valuable context (free, wash-filtered). Efficient and well-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?

Covers core purpose, usage, return content, and key behavioral notes (free, wash-filtered). Minor gaps like rate limits or pagination defaults are acceptable given schema details and lack of annotations.

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 baseline is 3. Description reiterates filter types but adds no significant new meaning beyond schema (e.g., 'free-text match' for search is already documented).

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?

Clearly states verb 'search', resource 'services', and specifics: filters, paginated list, stats, label mix. Distinct from siblings like x402_get_service (single service) and x402_check_wash.

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 'Use this to find services by topic, chain, or seller wallet' and mentions free tier without payment. However, no explicit when-not-to-use or alternatives aside from paid endpoints.

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