Clink Forge

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

With no annotations, the description carries the full burden, and it does disclose concrete behavioral traits: $0.01 per call settled via x402 (USDC on Base) and a response containing a provenance chain and Ed25519 attestation. It stops short of covering failure modes, rate limits, or auth prerequisites beyond payment.

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 zero waste: purpose first, then the payment and provenance details. Every clause earns its place and nothing is buried.

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-annotation, no-output-schema tool, the definition adequately covers what it does, its cost model, and its verifiability guarantees. It could still clarify what 'AQI categories' and the 'reporting area' mean, which matters for interpreting results.

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% for the single payment parameter, which already documents the base64 x402 header and the free-quote fallback. The description adds no parameter meaning beyond that, so the 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?

States a specific verb+resource: EPA AirNow observations aggregated into AQI categories with site counts per category. The aggregation framing implicitly distinguishes it from the sibling aqi_site_lookup, but it never names that alternative, so it falls short of full sibling differentiation.

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 explicit when-to-use or when-not-to-use guidance and no named alternatives. Usage is only implied by the 'aggregated into categories' framing versus the site-level lookup sibling, leaving the agent to infer the routing condition.

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 and does meaningful work: it discloses per-call cost ($0.005 via x402, USDC on Base) and that responses carry a provenance chain and Ed25519 attestation, which is real trust/verification context. It omits auth failure modes, whether payment is mandatory for a result, and any rate limits.

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 tight sentences, front-loaded with what the tool returns and followed by cost/trust metadata; there is no filler. It could be marginally better organized by separating the price/attestation clause from the data clause.

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 read-only lookup with no output schema, the description covers the returned fields, the cost model and the attestation guarantee, which is close to what an agent needs. The main gap is the required `id` parameter's format and a lack of routing guidance against sibling summary tools.

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 50% and the undocumented parameter is the required one: the description never explains what `id` is, its format, or how to obtain a valid site identifier beyond the vague phrase 'one monitoring site'. The free-quote/payment-header details live entirely in the schema, so the description adds almost no parameter meaning.

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?

States a specific verb+resource with scope: a current EPA AirNow observation for 'one monitoring site', returning AQI value, category and reporting parameter. The 'one monitoring site' scope implicitly separates it from the sibling aqi_category_summary, so an agent can distinguish them without opening either schema.

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 is only implied by the singular scope ('one monitoring site'), which suggests single-site point queries rather than aggregate summaries. It names no alternative tool and gives no explicit when-not condition, so routing against aqi_category_summary is left to inference.

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 behavioral burden, and it does meaningful work: it discloses the per-call price ($0.005), the payment rail (x402, USDC on Base), and the response's provenance chain plus Ed25519 attestation. It stops short of describing failure behavior on unpaid calls, rate limits, or whether any data is cached/refreshed.

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 what the tool returns and keyed on the identifier; the second sentence bundles pricing and response-trust details without padding. Dense and largely waste-free, though price and attestation could be split for faster scanning.

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 read tool with no annotations and no output schema, the description usefully lists the returned fields and covers cost/trust. It still omits the expected id format (numeric FDIC cert length vs. the schema's 12-char allowance) and does not define what 'lite' excludes relative to a fuller profile.

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 50%: the schema documents 'payment' but leaves 'id' as a bare string (maxLength 12). The description compensates by specifying that the identifier is an FDIC certificate number, which is genuinely new meaning the schema lacks. The schema already handles the legacy payment header 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?

States a specific resource and verb ('US bank profile... by FDIC certificate number') and even enumerates the returned fields (charter class, regulator, headquarters, established date, active status). It clearly differentiates from geographic UK sibling 'uk_company_lookup', but the 'lite' suffix implies a fuller variant whose relationship is never explained.

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 is implied by the resource ('US bank... by FDIC certificate number'), and no sibling overlaps with US bank data, so routing is unambiguous. However, there is no explicit statement of when to reach for this tool, what to do when the FDIC certificate is unknown, or any prerequisite/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?

With no annotations, the description carries the full burden and does disclose meaningful behavior: a per-call cost of $0.001, the x402 payment rail (USDC on Base), and that responses include a provenance chain and Ed25519 attestation. It stops short of stating error behavior, rate limits, or that this is a read-only operation.

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 tight sentences with the resource and returned fields front-loaded, followed by the cost and attestation details. Every clause earns its place, with only the dense billing clause being slightly packed.

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 correctly enumerates the returned fields, and it covers the pricing/payment model for the one parameter needing context. For a single-record lookup tool this is nearly complete, missing only id format specifics and error/not-found behavior.

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 50%, and the required 'id' parameter has no schema description at all; the description compensates by explaining it is composed of congress, type and number. The payment parameter is already documented in the schema (legacy header, omit for a free quote), and the description reinforces the paid nature. No exact id syntax/example is given, keeping it from a 5.

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 names a specific resource (US Congress bill record) and the lookup keys (congress, type, number), and enumerates the returned fields (title, sponsor, latest action, policy area, origin chamber). It is distinguishable from all siblings, none of which cover Congress bills, though it phrases purpose as a noun rather than an explicit verb.

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?

There is no statement of when to use this tool versus alternatives, no prerequisites, and no exclusions. The only usage hint is the incidental note that omitting payment yields a free quote, which concerns a parameter rather than tool selection.

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 the description carries the full burden, and it does well: it discloses pay-per-call pricing ($0.001 via x402/USDC on Base) and that responses include a provenance chain and Ed25519 attestation. It omits rate limits, failure behavior, and free-quote flow (which the schema's payment param implies), so it is strong but not complete.

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 dense sentences, front-loaded with what the tool returns and followed by cost/trust context; nothing is padding. A reader gets the resource, source, price, and response guarantees immediately.

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 no annotations, no output schema, and an undocumented required parameter, the description must do more work than it does. It covers response contents at a high level (index level, metadata, provenance, attestation) but leaves the year input format and result structure ambiguous.

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 only 50%: the required 'year' parameter has no schema description and its string/maxLength 7 format is never clarified in the description, even though 'by month' hints at granularity. The description adds meaning only for the response shape, not for the mandatory input.

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 names a precise verb+resource: monthly US CPI index levels plus series metadata for the national all-items series, sourced from BLS. Scope (national, all-items, monthly) clearly separates it from sibling series tools like state_gdp_series or electricity_retail_series, though it never names an alternative explicitly.

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?

There is no guidance on when to use this tool versus related series tools, nor any prerequisite or exclusion information. The payment/pricing sentence describes cost mechanics rather than selection criteria, so an agent gets no routing help.

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 cost ($0.001 per call via x402 on Base) and response provenance/attestation, which are valuable behavioral traits. However, it omits read-only confirmation, error handling, rate limits, and id validation details, leaving significant 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, front-loaded with purpose and return fields, followed by pricing and integrity details. Every sentence earns its place and there is no waste.

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 two-parameter lookup with no output schema, the description lists return fields and covers payment and attestation, making it largely complete. It still lacks guidance on how to source the recall number and when to prefer this over the monthly summary.

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 50%; the id parameter has no schema description, but the description supplies 'recall number' as its meaning. It also adds cost context for payment beyond the schema. It compensates for the coverage gap but does not specify id format or the free-quote option.

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 retrieves a CPSC recall by recall number and lists the fields returned (hazard, remedy, units affected, recall date). 'By recall number' implicitly distinguishes it from the monthly summary sibling, but the lack of an explicit verb and a named alternative keeps it from the top score.

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 when-to-use guidance or alternatives are provided. The description does not help an agent decide between this tool and siblings like cpsc_recall_monthly_summary or other recall lookups.

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 and does substantial work: it discloses pricing ($0.005/call, USDC on Base via x402), that a provenance chain and Ed25519 attestation are returned, and the free-quote-without-payment behavior. It does not say whether the dataset is periodically refreshed or how results are paginated.

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 tight clauses, front-loaded with the core capability. The billing/attestation sentence is dense but each element (price, provenance, signature) is a distinct decision-relevant fact.

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 low-complexity single-optional-param aggregation with no output schema, it covers what the tool returns (counts by hazard type by month), the cost model, and the payment flow. Missing only a stated time window and dataset freshness, which an agent would otherwise have to infer.

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 is only one optional payment parameter, and schema coverage is 100% with the deprecation and _meta preference already documented in the schema. With zero required parameters the baseline is 4; the description adds cost context but no new parameter meaning.

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 a specific aggregation: CPSC recalls per month counted by hazard type. This distinguishes it from cpsc_recall_lookup (record-level lookup). It does not explicitly name that sibling or distinguish lookup-vs-summary, keeping it just below a 5.

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?

Implicit usage as an aggregate-over-time view, and the 'over the current recall dataset' scoping is useful, but there is no explicit when-to-use vs. cpsc_recall_lookup, no stated time range, and no guidance on the free-quote path beyond what the parameter schema already says.

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 and does disclose meaningful behavior beyond structured fields: cost ($0.001 per call via x402, USDC on Base) and that responses carry a provenance chain and Ed25519 attestation. It omits failure/error behavior and what happens when payment is absent or invalid.

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 dense sentences, front-loaded with the core purpose and followed by the pricing/attestation facts. 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?

For a simple single-id lookup with no output schema, the description adequately covers what the tool returns and its payment model. It leaves minor gaps around identifier format and error/payment-failure behavior, but nothing critical to invoking it 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 50% (only 'payment' is documented, and its schema note already explains the free-quote fallback). The description adds cost context and implies the identifier is a CVE id via 'by CVE identifier', but gives no format detail (e.g. CVE-YYYY-NNNNN) beyond what the schema implies.

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 and resource (NVD CVE detail lookup by CVE identifier) and enumerates the returned content: description, CVSS metrics, CWE mapping and dates. This scope distinguishes it from siblings like kev_status_by_cve (KEV-only) and cve_published_daily_summary (daily aggregate).

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?

There is no when-to-use guidance, no mention of prerequisites, and no routing to alternatives such as kev_status_by_cve for exploit-status questions. The agent must infer usage purely from the tool name and sibling set.

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 usefully discloses cost ($0.01/call via x402, USDC on Base) and response traits (provenance chain, Ed25519 attestation), which are real behavioral value-adds. However, it doesn't describe what the summary actually contains beyond the severity bands, or any output shape, leaving meaningful gaps for a zero-annotation 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 tight sentences with zero filler; the core purpose is front-loaded and the payment/attestation context follows. Every clause carries 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?

No output schema and no annotations, so the description must do heavier lifting, and it does cover purpose, cost, and response attestation. It is slightly silent on the output shape (what the severity-band counts look like) and any time-window semantics, but for a no-required-param summary tool it is largely sufficient.

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 'payment' parameter, and the schema itself explains the x402 header and free-quote behavior. The description adds no further 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?

States a specific verb+resource+scope: 'CVEs published per day from the NVD feed, counted by CVSS severity band.' The aggregation-by-severity semantics clearly distinguish it from cve_detail_lookup and kev_status_by_cve, though it doesn't name those siblings explicitly.

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 when-to-use or when-not-to-use guidance is given, and no alternative tools are referenced. An agent must infer from the name/description that this is for aggregate daily counts rather than per-CVE detail. Sibling tools like cve_detail_lookup make a routing note genuinely useful here.

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 behavioral burden and does add real operational context: per-call cost ($0.001), payment rail (x402 USDC on Base), and that responses include a provenance chain and Ed25519 attestation. However, it omits error behavior, what happens for an invalid title, and payment 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?

Two tight sentences with no filler, front-loading the purpose before the commercial/response details. Well-sized for the schema complexity.

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 no output schema and no annotations, the description does list what the response contains (dates, provenance, attestation) and the cost model, which is helpful. Still missing id-format specifics and failure modes for a schema where the required parameter is undocumented.

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 50%; the 'id' parameter has no schema description (only maxLength 8). The phrase 'for one CFR title' partially compensates by implying id is a title identifier, but the exact format (numeric title, e.g. '1'–'50', or a name) is left ambiguous.

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?

States a specific resource (eCFR title status) and the exact data returned (latest amendment date and issue date for one CFR title). The purpose is clear, though it does not explicitly differentiate itself from any sibling tool by name.

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?

There is no when-to-use guidance, no prerequisites, and no mention of alternative tools. Usage is only inferable from the purpose statement (checking a CFR title's status), leaving the agent to guess the appropriate 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, and it does disclose real behavioral traits: per-call cost ($0.005), the payment rail (x402/USDC on Base), and that responses carry a provenance chain and Ed25519 attestation. However, it omits failure behavior, whether unattested/quote responses differ, and any rate or limit context, so it adds value without being complete.

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 tightly written sentences that lead with the data resource and follow with cost/response characteristics. Every clause earns its place with no redundancy, though the payment/attestation clause is secondary and slightly crowds the core purpose.

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 paid data-retrieval tool with no annotations and no output schema, the description conveys the data contents, cost, and response provenance, which is helpful. It still leaves parameter formats (entity codes, date format) and the shape of returned series undocumented, so an agent lacks enough to call it precisely.

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 25% (only 'payment' is documented), so the description must compensate. It loosely maps 'one state and sector' to the entity parameter and 'by period' to start/end, but gives no format, code scheme, or value guidance for those undocumented parameters, leaving a real gap.

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 names a specific source (US EIA retail electricity series), a scope (one state and sector), and the returned metrics (price, revenue, sales by period). This is far more than a restated name and clearly marks it as an energy-data series tool distinct from siblings like state_gdp_series or cpi_us_monthly. It does not explicitly contrast itself against a close alternative, keeping it just below a 5.

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?

There is no when-to-use, when-not-to-use, or alternative-selection guidance. The pricing mention ('$0.005 per call') implies paid access but does not tell the agent when to prefer this over another series tool. Usage must be inferred entirely from the resource description.

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, but it does add useful behavior: the $0.001 x402/USDC pricing, the free-quote option, and provenance chain plus Ed25519 attestation in the response. It omits error behavior, auth requirements beyond payment, and what happens when a recall number is not found.

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 then payment/attestation detail. No filler, though the pricing sentence serves a mixed purpose of billing and transparency.

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 correctly enumerates the returned fields (classification, reason, distribution, firm, status) plus the attestation. Payment cost is covered. Error/empty-result behavior is the only notable omission.

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 only 50% – the required 'id' parameter has no schema description at all, only a maxLength. The phrase 'by recall number' usefully clarifies that 'id' is a recall number, partially compensating, while the payment parameter is documented in the schema itself.

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?

States a specific verb+resource ('FDA enforcement action by recall number') and enumerates the returned fields, so an agent knows exactly what it retrieves. It does not explicitly distinguish itself from the sibling fda_recall_state_summary, which is the only real gap.

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 ('by recall number') but never states when to choose this over fda_recall_state_summary or the CPSC recall siblings, nor any prerequisites. No when/when-not guidance is provided.

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, and it does disclose meaningful traits: $0.01 cost via x402 (USDC on Base), a provenance chain, and an Ed25519 attestation. However it never explains how the single US state is supplied (the input schema exposes only 'payment'), which is a key invocation detail left opaque.

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 tight sentences: purpose and scope are front-loaded, followed by cost and provenance details. No wasted filler, though the payment/attestation clause is dense and could be split for clarity.

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?

No output schema exists, and while the description notes the response includes a provenance chain and attestation, the largest gap is that a summary 'for one US state' provides no way to know how to specify that state given the schema exposes only 'payment'. An agent cannot confidently invoke this 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% and the single 'payment' parameter is fully documented with its legacy header form and the free-quote omission case. The description adds only the $0.01 price, so baseline 3 is appropriate given the schema does the heavy lifting.

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?

States a specific verb+resource ('FDA recall counts'), the scope ('one US state'), and the grouping dimensions ('classification and product type') over a named dataset. This distinguishes it from fda_recall_lookup (a detail lookup) by virtue of being a summary, though no sibling is named explicitly.

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 when-to-use vs alternatives guidance, and no mention of fda_recall_lookup or the CPSC-equivalent summary tools as adjacent options. The 'for one US state' scoping implies a use case but there is no explicit routing or exclusion advice.

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 behavioral burden. It usefully discloses the cost ($0.001 per call via x402) and that responses include a provenance chain and Ed25519 attestation, but it omits what happens on missing/invalid payment, rate limits, or error 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?

The description is short and front-loads the resource and return fields, then adds payment/attestation context. Every clause contributes meaningful information, though the semicolon-joined payment clause could be slightly better integrated.

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 lookup with no output schema, the description covers the resource, returned fields, cost, and attestation. It lacks usage guidance and id formatting, but given the low complexity and the schema's payment description, it is reasonably 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 coverage is 50%: the 'payment' parameter is fully described in the schema, while 'id' is not. The description adds only that the id is a 'document number' and lists output fields, but does not clarify format, accepted syntax, or examples. This partially compensates for the coverage gap but remains minimal.

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 resource (US Federal Register document) and the lookup key (document number), and enumerates the returned fields. It distinguishes itself from siblings implicitly by resource specificity, but does not explicitly name or contrast with any sibling tool, so it falls short of a 5.

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?

There is no explicit when-to-use guidance, no alternatives, and no prerequisites. The phrase 'by document number' implies the necessary input but does not tell the agent when to prefer this tool over e.g. congress_bill_lookup or ecfr_title_status.

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 and largely does so: it discloses cost ($0.001 per call via x402/USDC on Base), the payment requirement, and that responses carry a provenance chain and Ed25519 attestation. It omits failure/error behavior (e.g., unknown area id) and any rate-limit or retry guidance, which keeps it short of a 5.

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 front-loaded sentences with no filler: the first establishes purpose and scope, the second covers cost and response guarantees. The second sentence is a dense run-on, but every clause (price, payment rail, provenance, attestation) 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?

With no output schema and no annotations, the description does cover pricing, payment, and response integrity, but leaves the critical input side under-specified — no id format, no way to find a valid id, no error behavior for a tool whose sole required parameter is an identifier.

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 50% — payment is documented (including the free-quote case) but 'id' has no description, only maxLength 40. The description hints that id identifies 'one metro or county area' but never states the expected code format (FMR area code vs. county FIPS), so it only partially compensates for the gap.

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 names a specific verb+resource: HUD Fair Market Rent, scoped to 'one metro or county area,' with rent broken out by bedroom count for the current fiscal year. The 'one area' scoping implicitly separates it from the sibling fmr_area_search, though it does not name that sibling explicitly.

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?

There is no when-to-use or when-not-to-use guidance. The obvious alternative, fmr_area_search, is never mentioned, so an agent has no stated path to obtain or disambiguate the required 'id' before calling lookup rather than search.

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 disclosure burden, and it does contribute real behavioral context: per-call pricing ($0.001 via x402/USDC on Base) and the presence of a provenance chain and Ed25519 attestation in the response. It still omits the free-quote path (left to the schema), the fact that this is a non-destructive read, and any error/limits behavior, so it is only partially complete for a no-annotation 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 tight sentences with the core capability front-loaded and no filler. The payment/attestation sentence earns its place given the absence of annotations, though it could be trimmed slightly.

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, but the description does state the return shape (areas plus rent schedules, provenance, attestation), which partly covers that gap. The missing pieces are the meaning of the required 'q' parameter and routing relative to fmr_area_lookup, leaving the definition merely adequate for a two-parameter 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 description coverage is only 50%: the required 'q' parameter has no schema description, and the description does not compensate by explaining its matching semantics (substring vs exact, case handling, 80-char cap). Only the optional 'payment' parameter is documented, and only in the schema, not the description.

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 gives a specific verb (Search) and resource (HUD Fair Market Rent areas), plus the match criterion (by name) and the shape of the result (matching areas with rent schedules). It does not, however, differentiate itself from the sibling fmr_area_lookup, which an agent could plausibly confuse with a name-search tool.

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?

There is no explicit when-to-use guidance, no when-not-to-use, and no mention of the sibling fmr_area_lookup as the alternative for exact/ID-based retrieval. Usage must be inferred from the name and description alone.

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 the description carries the full burden, and it does disclose meaningful traits: cost ($0.001 per call via x402/USDC on Base), and that responses carry a provenance chain and Ed25519 attestation. It stops short of explaining failure/payment-required behavior, which the schema partially covers.

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 tight sentences, front-loaded with purpose followed by cost/attestation details. Every clause adds information and nothing is redundant.

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 no output schema and no annotations, the description usefully enumerates the returned fields plus the provenance/attestation envelope and pricing. It is close to complete, missing only the expected id format and the free-quote path that the schema hints at.

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 only 50%; the payment parameter is documented in the schema, but the required 'id' has no description. The description implies id is a CVE identifier ('for one CVE') but gives no format (CVE-YYYY-NNNN) or bounds, so it only marginally compensates for the coverage gap.

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?

States a specific verb and resource ('CISA Known Exploited Vulnerabilities status for one CVE') and enumerates the exact fields returned (catalog membership, due date, required action, ransomware flag). An agent can distinguish it from sibling cve_detail_lookup because it is scoped to the KEV catalog only.

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 (single-CVE KEV check) but never states when to prefer it over cve_detail_lookup or cve_published_daily_summary, nor any exclusions. Context is inferable but no explicit routing guidance is given.

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 behavioral burden and does disclose notable traits beyond the schema: per-call cost ($0.001 via x402, USDC on Base), that the response carries a provenance chain, and an Ed25519 attestation. It does not state whether the call is read-only or what happens when the payment header is absent, but the payment/auth and provenance disclosures are genuinely useful context the structured fields do not supply.

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 dense sentences with no filler; the functional scope is front-loaded before the payment/attestation details. Nothing pads or repeats what the name or schema already says.

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-required-parameter, no-output-schema tool with no annotations, the description covers purpose, cost and attestation adequately. However, it never explains how 'one state' is determined when no state parameter exists, and it is silent on read-only semantics and non-payment behavior, leaving real gaps 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 coverage is 100% and the sole parameter (payment) is fully documented in the schema, so the baseline of 3 applies. The description adds no parameter-level detail and, in fact, implies a state selector that the schema has no field for, a minor semantic mismatch rather than added clarity.

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+resource ('Active US National Weather Service alerts for one state, aggregated by severity, urgency and event type'), clearly identifying both source and aggregation shape. It is distinguishable from generic data siblings like state_population_lookup or usgs_quake_lookup. The only weakness is that 'for one state' implies an input selector that the schema does not expose, leaving a small ambiguity about scope.

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 no when-to-use guidance, no prerequisites, and no routing to or away from alternatives despite a dense sibling list. It only states what the tool returns and what it costs, so the agent must infer applicability entirely from the name.

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 and does substantial work: it discloses the billing model ('charged the product's listed price per call via x402 (USDC on Base)') and what the response contains (provenance chain, Ed25519 attestation). It omits failure/refund behavior and rate limits, but the cost and payment disclosures are exactly the kind of context annotations would otherwise have to supply.

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 filler; the core action comes first and the routing pointer and payment/response details follow. Every clause carries information an agent needs.

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 no output schema the description must characterize returns, and it does so at a high level (provenance chain, attestation) though not the actual payload shape. Combined with the cost model and the search_catalog pointer, an agent has enough to invoke it, but the 'params' object's expected keys remain underspecified.

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 67% and the description adds real meaning on top: it establishes that 'slug' selects the catalog product and that slugs/prices/params are sourced via search_catalog, and it frames 'params' as the product's own query params. The payment parameter is already documented in the schema, so credit there is limited.

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 and resource ('Buy one call of any catalog product by slug') and immediately delimits scope ('including datasets that have no tool of their own'). An agent can distinguish this from the sibling search_catalog without opening either schema.

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 routes the agent explicitly to search_catalog for finding slugs, prices and params, and clarifies which products are reachable through this tool. It stops short of stating when NOT to use it (e.g. when a dedicated sibling tool already exists), so it is clear context rather than full when/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?

With no annotations, the description carries the burden and does well: it declares 'Free' (cost behavior), describes the return payload (slug, price, input schema, example params), and explains the downstream purchase flow. Missing explicit info on paging or result limits, but overall strong disclosure for a read-only search.

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 dense sentence front-loads the essential info and the follow-up action. No filler; every clause 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?

For a 2-param search tool with no output schema, the description covers cost, search scope, return fields, and next steps. The only gap is parameter-level detail for 'limit', but overall it 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 0%, so the description must compensate. It says the query searches by keyword across agency, dataset or topic, which adds meaning to the required 'query' param, but says nothing about the optional 'limit' or the maxLength constraint, leaving a coverage gap.

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?

States a specific verb (search) and resource (full Clink Forge catalog), and names the searchable dimensions (agency, dataset, topic). This distinguishes it clearly from sibling lookups like query_product or aqi_site_lookup, which appear to be targeted lookups.

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?

Provides clear usage context: it's free, returns products, and then explicitly routes the agent to buy via a product's own tool or query_product. It gives a follow-up path but does not state when NOT to use this search vs a direct lookup sibling.

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, and it discloses material behavior: paid access at $0.001 per call via x402 (USDC on Base), plus a provenance chain and Ed25519 attestation in the response. It omits error/rate-limit behavior and does not state that omitting payment yields a free quote (that lives only in the schema), but the cost and trust model are unusually well surfaced.

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, purpose front-loaded, followed by the commercial and trust terms. No filler; every clause conveys information an agent could act on.

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?

No output schema exists, so the description must describe returns, which it does (five record fields plus provenance and attestation). Payment semantics are covered at the description level. Slightly incomplete only in that no identifier format or failure mode is given.

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 50%: 'payment' is documented in the schema, while 'id' has none. The description's 'by identifier' provides weak compensation by implying 'id' is the SPDX license identifier, but it adds no format, casing, or valid-value guidance beyond that. Baseline 3 fits.

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?

States a specific verb+resource ('Canonical SPDX license record by identifier') and enumerates exactly what the record contains: full name, OSI/FSF approval status, deprecation flag and reference URL. It is trivially distinguishable from every sibling, which all address different data domains.

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 'by identifier' implies the tool is selected when you already hold an SPDX identifier, but there is no explicit when-to-use statement, no exclusions, and no named alternative (e.g. a license search by name). Usage is only implied.

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 and does notable work: it discloses pricing ($0.005/call via x402 on USDC/Base) and response trust features (provenance chain, Ed25519 attestation). It omits rate limits, retry/payment-failure behavior, and confirmation that the operation is read-only, but the cost and attestation details are genuinely useful 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?

Two tightly packed sentences with the core subject front-loaded and no filler. Dense but appropriate; 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 paid data-series tool with no output schema and no annotations, the description adequately covers what is returned (GDP types, per-state, per-year) plus payment and attestation, but omits parameter formats, pagination, and any usage conditions, leaving real gaps an agent would want filled.

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 only 25% (only 'payment' is documented), so the description must compensate. It loosely maps 'by year' to start/end and 'for one state' to entity, but gives no format details (e.g., state FIPS/abbreviation for entity, date format for start/end), leaving the two temporal params and entity largely undocumented.

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?

States a specific resource (US BEA state GDP series), scope (real and current-dollar GDP, by year, for one state), and source. An agent can clearly tell what it returns, though it does not explicitly differentiate itself from sibling series tools like electricity_retail_series or cpi_us_monthly.

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?

There is no explicit when-to-use or when-not-to-use guidance, and no alternative tool is named. The mention of cost and payment describes mechanics rather than selecting conditions for the tool, leaving usage entirely to inference.

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 and does disclose notable traits: pricing ($0.001/call), the x402/USDC-on-Base payment path, and that responses include a provenance chain and Ed25519 attestation. It stops short of failure modes or rate limits, but the payment/trust disclosure is well beyond what structured fields give.

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 tightly packed sentences with no waste; the core purpose is front-loaded, followed by the payment/response context. Every clause 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?

No output schema and no annotations, so the description should do more. It hints at response contents (vintage, series, provenance, attestation) but never describes the actual return fields or the id's format, leaving gaps for a data-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 50%: payment is documented in-schema, but `id` is not. The description partially compensates by implying the id spans a state plus 'vintage and series identifiers,' giving the agent a clue about the 4-character id's composition, though not its exact syntax.

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?

States a specific verb+resource: 'US Census Bureau population estimate for one state,' which clearly identifies what data is returned. It doesn't explicitly name or differentiate against the closest sibling (state_gdp_series) or other state-level lookups, but the resource 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?

No when-to-use guidance, no alternatives named, and no exclusions. The agent must infer from the name alone that this is the population dataset versus e.g. state_gdp_series.

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, and it does add real behavioral context: cost ($0.001 per call), payment rail (x402 USDC on Base), and that responses include a provenance chain and Ed25519 attestation. However, it omits failure behavior, rate limits, and how payment/auth actually gates a call beyond the cost line.

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 tight sentences with the core capability front-loaded, followed by cost and response guarantees. No filler, though the payment/provenance clause is compressed and could be slightly clearer about required vs optional payment.

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 no annotations, no output schema, and 4 params at 25% coverage, the description leaves key gaps: how to identify the target station and the required date formats. For a paid, parameterized data-retrieval tool this is under-specified.

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 only 25% (just the payment param), so the description must compensate and largely does not. It never explains that 'entity' identifies a station, nor the format/semantics of 'start'/'end' (maxLength 12, likely YYYY-MM for GSOM monthly data) or that they form a date range.

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+resource (NOAA NCEI monthly average temperature, GSOM dataset) with a clear scope ('for one weather station') and lists what accompanies the result (station metadata, observation date). It is precise enough to distinguish the tool, though no sibling tool overlaps, so no differentiation work is needed.

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?

There is no when-to-use guidance, no exclusions, and no alternatives named. The single-station scope is implied by 'for one weather station', but an agent gets no help deciding this versus other data lookups or how to handle multi-station needs.

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 and does well: it discloses the cost ($0.005 per call), the payment rail (x402, USDC on Base), and response integrity features (provenance chain, Ed25519 attestation). It omits failure behavior for unknown/invalid company numbers and whether payment is strictly required versus optional for a quote.

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, zero filler. Identity and returned fields come first, and the pricing/provenance sentence follows — front-loaded and every clause carries information an agent needs.

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 no output schema and no annotations, the description compensates by listing the response fields and the payment/attestation metadata. It is close to complete for a single-record lookup, missing only error/edge-case behavior and identifier format rules.

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 50% and only two params exist. The description usefully clarifies that the required 'id' parameter is a company number, which the schema does not state, but adds nothing about the 12-character limit or accepted formats; the 'payment' param is already explained in its own schema description.

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?

States a specific verb+resource: 'UK Companies House company record', then enumerates the returned fields (name, status, incorporation date, type, registered office). It is clearly distinguishable from data-summary siblings, though it never explicitly differentiates itself from uk_new_companies_daily, which is the closest 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 phrase 'by company number' implies the lookup key, but there is no statement of when to use this tool versus uk_new_companies_daily or other UK datasets. No prerequisites, no exclusions, and no mention of the free-quote path that the schema exposes.

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 and does well on the operational side: it discloses a $0.01 per-call cost via x402 (USDC on Base), that omitting payment yields a free quote, and that responses carry a provenance chain and Ed25519 attestation. It stops short of defining the rolling-window length, data freshness/lag, or rate limits.

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 tight sentences with zero filler: purpose first, then cost and response properties. Front-loading is correct and every clause carries information, though the split of commercial details into a second sentence is slightly dense.

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-annotation, no-output-schema metric tool, the description covers the output properties (provenance, attestation) and the commercial model, which is above average. However, it leaves the unit of analysis underspecified — 'rolling window' is never quantified, and the shape of the returned counts (single value vs. series) is not stated, which an agent needs to call it 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% for the single 'payment' parameter, which the schema itself documents in detail (legacy base64 header, prefer _meta["x402/payment"], omit for free quote). The description adds nothing about the parameter beyond restating the pay-per-call model, so the 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?

States a specific verb+resource+measure: newly incorporated UK companies counted per day, sourced from Companies House advanced search. It is clearly distinguishable in substance from the similarly-named sibling uk_company_lookup (aggregate daily count vs. single-company lookup), though it never names that sibling explicitly.

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?

There is no when-to-use guidance and no alternatives. The closest sibling, uk_company_lookup, is never mentioned, so an agent must infer from the name alone whether it wants a daily count or a company detail lookup. The only usage signal is the implicit 'per day' time-series framing.

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 and does disclose real behavioral traits: cost ($0.001 per call), payment rail (x402/USDC on Base), and that the response carries a provenance chain and Ed25519 attestation. The one gap is that 'for one date' is not reconciled with the start/end parameters in the schema.

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 front-loaded sentences with no filler: what is returned first, then pricing and provenance. Efficient, though the 'for one date' framing is slightly imprecise given the range-style parameters.

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 and no annotations, so the description must do everything; it does cover cost, payment, and response authenticity, but it never explains the start/end parameters or whether a date range is supported. Adequate but with a material gap for a paid 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 only 33% and the start/end parameters have no description in either the schema or the description, leaving how date scoping works unresolved. The description even asserts 'for one date', which sits awkwardly beside a start/end pair; only the payment parameter gains indirect context from the pricing sentence.

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 names a specific verb+resource ('US Treasury Debt to the Penny record') and enumerates the exact contents returned (total public debt split into intragovernmental holdings and debt held by the public). It is immediately distinguishable from time-series siblings like cpi_us_monthly or state_gdp_series.

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 'for one date' implies the use case is a single-date query, which implicitly contrasts with the series-based siblings, but no alternative tool is named and no when-not condition is stated. This is implied usage rather than explicit 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 present, the description carries the full burden and does unusually well: it discloses that the tool is metered ($0.001 per call via x402/USDC on Base) and that responses carry a provenance chain and Ed25519 attestation, which shapes agent trust decisions. It omits failure behavior for unknown ids and any latency/rate-limit context, keeping it short of a 5.

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, zero filler, with the core lookup purpose front-loaded before the payment and attestation details. Every clause carries distinct 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?

There is no output schema, so the description must communicate return content, and it does by enumerating the event fields plus the provenance/attestation envelope. What remains thin is the id format and the not-found/no-charge case, which an agent would need to call confidently.

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 50%: the payment parameter is documented in the schema, but the required id parameter has no description at all. The phrase 'USGS earthquake event by event id' adds partial meaning (it is a USGS event identifier), but no format example or validation hint compensates for the gap. Baseline 3 for a half-covered schema 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 names a specific resource (a USGS earthquake event) and the lookup key (event id), then enumerates the returned fields (magnitude, depth, place, origin time, alert level). An agent immediately knows this is a point lookup, not a search or aggregate. It does not need to differentiate from siblings since no other quake tool exists in the sibling list.

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?

There is no statement of when to use this tool versus alternatives, nor any prerequisites or exclusions. The only usage-adjacent content is the cost disclosure ($0.001 per call), which tells the agent the call is paid but not when it is the right choice.

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 and does disclose meaningful behavior: a metered cost ($0.001 per call via x402/USDC on Base) and that responses carry a provenance chain plus an Ed25519 attestation, which signals verifiability/trust properties. It omits edge behavior (invalid/unknown ISO code handling, rate limits, payment failure modes), so it falls short of a 5.

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 dense sentences with zero filler, and the purpose is front-loaded ahead of the payment/provenance caveats. The payment and attestation clauses are compressed but each still carries distinct information, so it stops just short of ideal structure.

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 no output schema and no annotations, the description must carry the response contract, and while it names the top-level fields and the attestation, it does not describe structure, error behavior, or what a 'free quote' response contains. For a paid tool where callers need to reason about cost and payment failure, this leaves real 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 coverage is only 50%: the required 'id' parameter has no schema description (only maxLength 8), and the description compensates by specifying it is an ISO code, resolving an otherwise opaque key. The optional 'payment' parameter is explained in the schema, not the description, so the description does not fully cover both 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?

States a specific verb+resource and the lookup key: 'World Bank country record by ISO code.' It also enumerates the returned fields (region, income group, lending category, capital, coordinates), so an agent knows exactly what this retrieves. No sibling covers World Bank country data, so no differentiation is required.

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?

There is no when-to-use guidance, no mention of alternatives, and no stated preconditions or exclusions. Usage is only inferable from the name and the 'by ISO code' phrasing. This matches the calibration's 2 for 'no when-to-use, no prerequisites.'

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