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

With no annotations, the description carries the full burden. It discloses the payment mechanism ($0.02 USDC via x402) and the fallback behavior without WALLET_PRIVATE_KEY. However, it does not describe the response structure, error handling, or side effects, leaving gaps.

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

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

Two sentences, no fluff. The first sentence states core functionality, the second adds critical behavioral context. Information is front-loaded and 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 tool's complexity (payment, multiple metrics, no output schema), the description is adequate but incomplete. It lists returned data dimensions but not their format, lacks error scenarios, and does not clarify how the payment challenge works in detail. Sibling tools are not referenced for context.

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

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

Schema description coverage is 100%, so the schema already documents both parameters. The description repeats the schema examples without adding new meaning. Baseline 3 is appropriate as the description adds no semantic value beyond the schema.

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

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

The description clearly states the tool's purpose: retrieving demand depth for a category, listing specific metrics (volume, sources, buyer-class share, price points, daily series). It uses a specific verb+resource pattern and distinguishes from siblings like get_intent_reports and get_network_stats.

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

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

The description implies usage when category demand data is needed but lacks explicit when-to-use or when-not-to-use guidance. It mentions payment requirements but does not compare with sibling tools or provide exclusion criteria.

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

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

No annotations are provided, so the description bears the full burden. It discloses key behaviors: returns a funnel report for a service, and without proper authentication/payment returns a challenge. It does not detail output format but is sufficiently transparent.

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

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

The description is a single, dense sentence that efficiently conveys purpose and payment model. No unnecessary words, well-structured with front-loaded action description.

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 only two parameters and no output schema, the description adequately covers what the tool does, its prerequisites (key or payment), and the fallback behavior. It could mention return format but is complete enough for an agent.

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

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

Schema coverage is 100%, so the schema already documents both parameters. The description adds no additional semantic detail about the 'service' or 'window' parameters beyond what is in the schema, just pricing context about the key binding.

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: generating an intent report funnel for a specific service, listing components like bounce funnel, traffic classes, etc. It distinguishes from siblings like get_intent_trends by focusing on a single service's funnel.

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

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

The description explains when to use the tool based on payment model (free with key, otherwise paid) and mentions the alternative of returning a payment challenge without proper credentials. It does not explicitly compare to siblings, but the context is clear enough.

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

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

With no annotations, the description discloses critical behavior: payment required ($0.01 USDC on Base via x402) and conditional response (payment challenge vs. settled data). This goes beyond the schema but could mention rate limits or failure handling.

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

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

Extremely concise: two clear sentences front-loading the critical payment behavior, with 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?

Given 2 parameters, no output schema, and no nested objects, the description explains purpose and unique behavior. It hints at output (top endpoints/categories) but could be more explicit about response structure.

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 adequate parameter descriptions (limit, window with default and enum). The description adds no extra parameter meaning, so baseline 3 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 clearly identifies the resource ('top requested x402 endpoints and categories by autonomous agents') and the action ('get'), with specific detail about splitting by traffic class. This distinguishes it from sibling tools like 'get_category_demand' and 'get_intent_report'.

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

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

The description implies usage context through payment requirements (with or without key) but does not explicitly state when to use this tool over alternatives or provide when-not scenarios.

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 the description carries full burden. It mentions 'Live' totals and 'Free', but does not disclose idempotency, authentication needs, rate limits, or other behavioral traits.

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 short but includes a specific number ('402 responses observed') that may be confusing as a static example rather than a live value. It could be more general.

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?

Without an output schema, the description should explain the return structure. It lists counters but does not clarify if these are all fields or just a sample, leaving 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 schema has zero parameters, so the description adds value by listing the specific counters returned (responses observed, agent-class requests, etc.), providing context beyond the empty 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 it provides 'live totals for the ForgeMesh machine-commerce network' and lists specific counters, distinguishing it from sibling tools like get_network_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?

No guidance on when to use this tool versus alternatives. The only contextual clue is 'Free', but no mention of recommended use cases or prerequisites.

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 description carries full burden. It discloses the paid nature ($0.005 USDC via x402) and the conditional behavior that without WALLET_PRIVATE_KEY it returns a payment challenge instead of data. This is valuable beyond basic stats listing.

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: first covers payment and stats content, second explains alternative behavior. No redundant information, every sentence adds value.

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

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

Given no output schema and no nested objects, description adequately covers the key aspects: payment, data content, and conditional behavior. Misses rate limits or update frequency, but overall complete for a simple read operation.

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 with 100% coverage, so baseline is 4. Description adds meaning by stating it returns 'network-wide' stats, confirming no filtering parameters are needed. No additional parameter details required.

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 it retrieves network-wide intent stats including total events, services, traffic classification, and ad activity. While it doesn't explicitly differentiate from sibling tools like get_category_demand or get_intent_report, the specific resource 'network stats' and mention of payment model make the purpose distinct enough.

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

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

No guidance on when to use this tool versus alternatives. It mentions payment and behavior without wallet key, but does not specify context prerequisites or scenarios for choosing this over sibling 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 exist, so description carries full burden. It mentions the tool is free and returns canonical terms and complete disclosure. However, it lacks details on authentication, rate limits, or response format. Adequate for a simple read-only 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?

Two concise sentences (20 words) with no filler. Front-loaded with 'Free.' First sentence gives core info, second adds precision. Every word earns its place.

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

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

Tool is extremely simple (0 params, no output schema, no annotations). Description fully captures what it does. Could hint at response format, but is complete enough for an agent to invoke correctly.

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

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

Schema has no properties (100% coverage by default). Description adds no parameter details, but none are needed. Per calibration, high coverage gives baseline 3.

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

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

Description clearly states verb 'get' and resource 'terms of service and complete data-collection disclosure'. It distinguishes itself from sibling tools like 'get_category_demand' and 'get_network_stats' by focusing on legal/informational content.

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

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

Although no explicit alternatives or exclusions are mentioned, the tool's unique purpose (terms & data disclosure) makes its usage self-evident. The 'Free.' tag hints at no cost for invocation. Sibling tools are clearly different in domain.

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, and the description only mentions 'Free.' and the output composition ('sponsored + similar x402 services'). It does not disclose behavioral traits such as side effects, authorization needs, rate limits, or read-only nature. This is insufficient for a tool with no annotation support.

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, consisting of two sentences that front-load the key information (free, purpose, inputs). Every word earns its place; no redundant or vague phrasing.

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

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

Given the tool has full schema coverage, no output schema, and no annotations, the description provides sufficient clarity on purpose and inputs. It mentions the output composition but lacks details on the exact format. It is adequate for a low-complexity 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 each parameter described. The description adds context beyond the schema (e.g., self-exclusion for service, sponsored + similar for category/endpoint). It slightly improves the understanding of 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 identifies the tool's purpose: to preview the recommendations block for the x402-ads middleware. It specifies the action ('See'), the resource ('typed recommendations block'), and the inputs ('endpoint and category'). It distinguishes itself from sibling tools which are analytics/reporting 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 when wanting to preview recommendations, but does not provide explicit guidance on when to use this tool versus alternatives (e.g., get_category_demand). No exclusions or prerequisites are mentioned.

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