x402-list-mcp

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

With no annotations, the description carries full burden. It discloses that the tool is read-only (checking live health), returns per-service status, uptime windows, response time, consecutive failures, and daily snapshots. It also notes 'No money fields'. Missing details like auth requirements or rate limits, but these are less critical for a health check.

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, front-loaded with purpose, each sentence adds value. No redundant 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 relatively simple tool with 2 params and no output schema, the description fully covers both modes, returned fields, and constraints. Missing error handling details but acceptable for a health check.

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%, but the description adds significant meaning: it explains the effect of slug (directory vs single service) and uptime_period default and purpose. It also adds context like 'No money fields', which is not in the schema.

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

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

The description clearly states the tool checks live health of x402 services, distinguishing between directory-wide snapshot (no slug) and single-service detail (with slug). It specifies returned fields (status, uptime, response time, failures) and explicitly mentions 'No money fields', differentiating from siblings like get_service or find_best_service.

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

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

The description provides clear context for when to use without slug (directory snapshot) vs with slug (single service details). However, it does not explicitly mention alternatives among sibling tools or specify when not to use this 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?

Without annotations, the description discloses the ranking logic and exclusions (settlement volume is per-facilitator). It also explains the optional facilitator context. This adds transparency about what the tool does and does not do.

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

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

Two sentences, front-loaded with purpose and constraints. No redundant or unnecessary 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 8 parameters and no output schema or annotations, the description covers the core ranking and exclusions well. It does not describe return format, but the context is sufficient for an agent to understand the tool's capabilities.

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. The description adds context about ranking fields and the volume caveat, but does not significantly expand on individual parameter semantics beyond the schema descriptions.

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

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

The description clearly states it recommends best x402 services ranked by specific fields (live status, verification, uptime, response time, price) and filtered by category and network. It distinguishes from siblings like search_x402_services and get_facilitator_volumes.

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

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

The description provides clear context for when to use (ranking by reliability and price) and explicitly states what it doesn't track (settlement volume per service). It also mentions optional facilitator context. However, it does not explicitly list alternatives or when not to use.

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 burden of behavioral disclosure. It explains the return data (USD volume, tx counts, verification flag, optional timeseries and per-chain breakdown), but does not mention any destructive actions, auth requirements, or rate limits. It adds moderate behavioral context.

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 very concise at two sentences, each packed with meaning. It front-loads the core purpose and immediately provides key details (metrics, timeframes, optional includes). 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?

The description covers the main return values and optional expansions (timeseries, per-chain). However, it lacks details on pagination behavior (page/per_page) and the exact structure of the timeseries or breakdown. Considering the lack of output schema, it is reasonably complete for a data retrieval tool.

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

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

Schema description coverage is 67%, and the description adds value by explaining that the 'timeframe' parameter 'drives the sort order of the returned facilitators,' which is not in the schema. It also clarifies that 'days' is only used when 'include_timeseries' is true, reinforcing the schema.

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

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

The description clearly states the tool's purpose: getting on-chain-verified settlement volume per x402 facilitator. It specifies the metrics returned (USD volume, transaction counts for various timeframes, and a verification flag). It also distinguishes itself by noting 'PER-FACILITATOR, not per-service'.

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

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

The description does not provide explicit guidance on when to use this tool versus its siblings (e.g., check_health, get_service). It only mentions it's the 'core x402-list metric', but no when-to-use or when-not-to-use instructions.

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 full burden. It describes the output fields but does not explicitly state that the tool is read-only or non-destructive. While 'get' suggests safety, a direct statement would improve transparency. Discloses important price unit nuance.

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 wasted words. Front-loaded with the tool's purpose and output details, followed by usage guidance and a critical clarification about price units. Highly 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 complexity (single parameter, no output schema), the description adequately covers what the tool returns by listing key fields and addressing price interpretation. Minor omission: no mention of error handling or performance characteristics, but acceptable for a detail lookup tool.

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

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

Schema coverage is 100% with a clear description for slug. The description adds the phrase 'by slug' but does not provide additional semantic value beyond what the schema already offers. 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 retrieves full details for one x402 service by slug, listing specific fields (live status, uptime, avg response time, networks, asset, priced endpoints). It explicitly distinguishes itself from search_x402_services by indicating this tool is used after that one for inspection.

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 states 'Use after search_x402_services to inspect a specific service', providing clear sequencing context. Also clarifies price interpretation, which aids correct usage. Lacks explicit when-not-to-use or alternatives, but the positive guidance is strong.

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 discloses that verified_only filtering is client-side and that prices are in USD. It clearly describes the search and filter behavior. However, it does not specify whether the operation is read-only (no annotations), but the context implies it is safe.

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

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

The description is two sentences, front-loaded with the core purpose, followed by concise details on filters, sorting, and return fields. 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?

The description covers the main functionality, filters, sort, and return fields. It references 'categories context' for category names, implying additional context is needed. It does not explain pagination behavior or error handling, but for a parameter-rich search tool with no output schema, it is nearly complete.

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

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

The description adds meaningful context beyond the input schema: it lists sort options (newest, uptime, cheapest, endpoint count) and notes that prices are in US dollars. With 75% schema coverage, the description enhances understanding, particularly for the sort and verified_only 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 clearly states the tool searches and filters a specific directory (x402-list) for services accepting x402 payments. It lists filter criteria (free-text, category, network, status), sort options, and return fields, distinguishing it from sibling tools like 'get_service' which returns a single service.

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 searching/filtering but does not explicitly contrast with siblings such as 'find_best_service' or 'check_health'. No guidance on when to use this tool vs alternatives is provided.

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