StatePulse API

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

With no annotations, the description must carry full burden. It discloses the checks performed (revert simulation, gas balance, Base gas) and output (verdict with reasons). It implies read-only behavior but does not explicitly state non-destructive nature or any side effects.

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 front-loaded with core purpose and output, followed by a list of search keywords. No wasted words, efficient and clear.

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 moderate complexity and no output schema, the description adequately explains the tool's function and output. It doesn't cover error conditions or edge cases but the verdict-with-reasons output implies handling. Context from siblings supports completeness.

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

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

Schema coverage is 100%, so baseline is 3. The description adds no additional meaning beyond the schema's parameter descriptions. No extra constraints or formatting details are provided.

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 pre-flights an onchain transaction by simulating, checking gas balance, and reading Base gas, returning a GO/NO_GO verdict. It differentiates from siblings by explicitly noting it replaces three separate calls (simulateTransaction, getWalletBalances, getGasHistory).

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: before transacting, as a consolidated alternative to three separate tools. It provides search keywords but lacks explicit exclusions or when-not-to-use guidance.

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

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

No annotations are provided, so the description carries full burden. It discloses the query method (Cloudflare DoH) and the record types queried, but does not mention potential rate limits, error behavior, or data formatting. This is adequate for a simple read-only query but lacks detail on what happens during failures.

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, front-loaded sentence that efficiently conveys the action, record types, and query method. Every word serves a purpose with no 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?

No output schema is provided, so the agent is left uninformed about the return value structure. While the tool is simple (DNS query), the missing output format weakens completeness. The description adequately covers what and how but not what the agent can expect to receive.

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 the domain parameter already described. The description adds value by specifying the query purpose (DNSSEC and CAA records) and the use of Cloudflare DoH, providing context beyond the schema's 'Domain name to audit'. This helps the agent understand the parameter's role in a specific security audit.

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 uses the specific verb 'Queries' and identifies the exact resources: DNSSEC (DS) and Certification Authority Authorization (CAA) records for a domain. This clearly distinguishes it from sibling tools like checkDnsPropagation or auditNetworkHost, which serve different purposes.

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

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

The description implies usage for auditing security DNS records but provides no explicit guidance on when to use this tool vs alternatives (e.g., checkDnsPropagation for general propagation). No exclusions or contextual cues are 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 must convey behavioral traits. It states it 'Scans' and 'audits', implying read-only operation, but doesn't mention any side effects, rate limits, or prerequisites. The claim 'Safest and most effective for risk analysis' adds little factual transparency.

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

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

The description is concise, consisting of a single core sentence and a keyword line. It is front-loaded with the action and resource. The only minor issue is the somewhat promotional 'Safest and most effective' phrase, but overall it is 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 no output schema, the description should provide context on what the scan returns (e.g., a report, scores, pass/fail). It omits this entirely, leaving the agent uncertain about the output format and how to use the 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?

The input schema already fully describes the single required parameter 'host' with an example and description. The tool description does not add any semantic value beyond the schema, meeting the baseline for 100% schema coverage.

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 scans a host to audit multiple security and compliance aspects (DNSSEC, SSL, headers, geodata), and the 'Matches' keywords provide use cases. It combines several checks into one tool, but doesn't explicitly differentiate from sibling tools like auditDnsSecurity or checkSslExpiry.

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 'Matches' list gives example usages (network security audit, scan website ports, etc.), implying scenarios where to use this tool. However, it lacks explicit guidance on when not to use it or alternatives for single-aspect checks.

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

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

No annotations are provided, so the description carries full burden for behavioral disclosure. It only states it fetches and scores headers but does not mention authentication needs, rate limits, error handling, or whether the operation is read-only (e.g., no warning about potential cost or side effects).

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 sentence that efficiently conveys the tool's purpose and scope with no redundant words. It is front-loaded with the verb and resource.

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

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

For a tool with one required parameter, no output schema, and no annotations, the description is minimally adequate. It lacks details on return format (e.g., what the score looks like), error scenarios, or how the scoring is performed, which could be useful for a security audit 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?

The single parameter 'url' is described in the schema as 'Target website URL', and the description adds context about fetching headers for scoring. Since schema coverage is 100%, the description adds moderate value but does not enhance the parameter's meaning 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 fetches URL headers to score security configurations like HSTS, CSP, and X-Frame-Options. The specific verb 'Fetches' and resource 'target URL headers' differentiate it from sibling tools like auditDnsSecurity or checkSslExpiry.

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 use for scoring security headers but provides no explicit when-to-use or when-not-to-use guidance. No alternatives or exclusions are mentioned, leaving the agent to infer context from the tool name 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 are provided, so the description carries full burden. It discloses that the endpoint is free and automatically logs unmatched needs as roadmap requests, which are important behavioral traits. No contradictions.

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 wasted words. Front-loaded with key info ('FREE endpoint'), then a concise explanation of the function.

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 simplicity (3 parameters, no nested objects, no output schema), the description is sufficiently complete. It explains input, what is returned, and side effects (logging).

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

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

Schema coverage is 100%, so baseline is 3. The description adds context beyond the schema by stating the endpoint is free and that unmatched needs are logged, which enhances understanding of the 'needs' and 'agent_contact' parameters.

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

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

The description clearly states the verb 'submit' and resource 'array of data or capability needs', and explains what the API does: return matching endpoints and log unmatched needs as roadmap requests. This distinguishes it from sibling tools that retrieve specific data.

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 checking if capabilities exist but does not explicitly state when to use this tool versus alternatives, nor does it provide exclusions or when-not-to-use 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 full burden. It indicates a read operation ('Checks') but does not disclose any behavioral traits such as side effects, rate limits, authentication requirements, or what 'propagation status' entails. The description is minimal.

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?

Single sentence that is concise and front-loaded with the verb and key information. No redundant words or filler. Every word 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?

Despite lacking annotations and output schema, the description covers the essential purpose and input parameters adequately for a simple propagation check. However, it omits details on the response structure, error cases, or interpretation of results, which may be needed for full agent utilization.

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 2 parameters with 0% coverage. The description adds meaning by listing record types (MX, TXT, A, CNAME) which likely correspond to the 'type' parameter, and 'domain' is implied. However, it does not provide explicit mapping or format constraints, so the description partially compensates.

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 verb ('Checks'), resource ('global ... propagation status'), and specific record types (MX, TXT, A, CNAME) using a specific method (Cloudflare DoH endpoints). It distinguishes from sibling tools like auditDnsSecurity or lookupWhois by focusing on propagation status.

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 when to use (checking propagation of specified record types) but does not explicitly state when not to use or suggest alternatives like auditDnsSecurity for deeper analysis. No guidelines on prerequisites or 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?

No annotations provided. The description mentions using public certificate-transparency logs, indicating a read operation. However, it lacks details on rate limits, authentication, or potential side effects, though these are likely minimal.

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 well-structured sentence that efficiently conveys the tool's purpose with no superfluous text.

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

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

The description is adequate for a simple tool with one parameter. It clearly defines the input and what is extracted. Lack of output schema is not critical here as the extraction result is implied.

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 description does not add extra meaning beyond the schema's 'domain' parameter with examples. A baseline score of 3 is appropriate.

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

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

The description clearly states the tool's action ('Extracts certificate validity dates and expiration countdown') and subject ('a domain'), distinguishing it from siblings like auditSecurityHeaders and auditDnsSecurity.

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

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

The description implies usage for checking SSL expiry. No explicit when-not-to-use or alternatives, but the context is clear given the tool's name and sibling list.

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

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

No annotations provided, so description carries the full burden. It discloses the data source (Open-Meteo Geocoding) but does not mention error handling, rate limits, or what happens for invalid cities. Behavioral traits beyond the purpose are minimal.

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?

Single sentence, front-loaded with the action, no fluff. Every word contributes to understanding the tool's 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 simple tool with one parameter and no output schema, the description adequately covers outputs and data source. It could mention the format of the result, but the listed outputs (local time, offset, DST) give sufficient 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 coverage is 100%, so the description adds no additional meaning to the single parameter 'city'. Baseline of 3 is appropriate since the schema already describes it.

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

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

Description uses a specific verb 'resolves' and identifies clear outputs: local time, offset, and daylight savings status. The resource (city name) and data source (Open-Meteo Geocoding) are stated, distinguishing it from sibling tools like checkDnsPropagation or checkSslExpiry.

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 guidance on when to use or avoid this tool. Usage is implied by the purpose (resolving timezone info for a city), but there is no mention of alternatives or prerequisites, which would be helpful given the many 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 are provided, so the description carries the full burden. It discloses that the search is against a 'daily-synchronized' index and clarifies the result is not a legal opinion, but it does not explicitly state read-only behavior or any other behavioral traits like auth needs.

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 with no wasted words; the core action and key disclaimer are front-loaded.

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 tool with one parameter and no output schema, the description is largely complete. It explains the purpose and limitation, though it could optionally mention the nature of the output.

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 parameter 'word', which has a description in schema. The tool description adds no additional parameter semantics beyond what the schema provides.

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

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

The description clearly states the verb 'performs' and the resource 'first-pass wordmark conflict search against USPTO trademark index', distinguishing it from related sibling tools like getPatentStatus.

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 sets clear expectations by noting it is a 'screening result, not a legal clearance opinion', but does not explicitly mention when not to use or suggest alternatives among siblings.

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?

Describes the deposit mechanism and non-custodial nature, but does not disclose potential side effects (e.g., funds locked irreversibly), failure modes, or required authorizations beyond the signature. No annotations present to supplement.

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 plus a keyword line. Essential information is front-loaded, no fluff.

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

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

For a blockchain tool with 9 parameters and no output schema, the description explains the mechanism and contract. Missing details about return value, confirmation steps, or error handling, but still fairly 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 descriptions cover all 9 parameters (100% coverage). The tool description does not add additional meaning or usage context to any parameter beyond what the schema already provides.

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

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

Description clearly states the action ('deposits a real USDC bounty'), specifies the blockchain (Base), the mechanism (EIP-3009), and the contract (EscrowRegistry). It distinguishes from the sibling 'releaseCoordinationBounty' by focusing on deposit.

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?

Keywords like 'deposit onchain bounty' imply usage context, but there is no explicit guidance on when to use this tool vs alternatives, prerequisites (e.g., having a valid signature), or when not to use it.

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?

Discloses fallback behavior and labeling of fallback data as live traffic, not confirmed arrivals. However, no annotations exist, and other behaviors (auth, limits) are omitted.

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 waste. Key information front-loaded.

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 tool with one parameter and no output schema, description covers purpose, sources, and fallback. Could mention return format or time range but not critical.

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 examples, so baseline 3. Description does not add extra meaning 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 it retrieves recent arrivals from two sources (OpenSky, Airplanes.live), using specific verbs and resources. It distinguishes itself from sibling tools like getFaaDelays.

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 guidance on when to use this tool versus alternatives. Among many data retrieval siblings, context is missing.

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 should disclose behavioral traits. It mentions 'live' and 'OpenAQ' as source, but fails to mention rate limits, data freshness, error handling for invalid coordinates, or whether the call is read-only (though likely safe). Minimal transparency beyond basic purpose.

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 sentence of 18 words, front-loading the core purpose and data source. No wasted words; every word serves a 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 simple 2-parameter tool with no output schema, the description adequately covers the what and where of inputs. However, it lacks any description of return values or behavior, which is a gap given no output schema.

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 0%, so description must compensate. It only mentions 'latitude/longitude' generically, without specifying format, range, or optionality (though both are required). The schema provides examples, but the description adds little meaning beyond what the schema already 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 clearly states it retrieves 'live localized air quality indices (AQI) and pollutant levels' for a lat/lng using OpenAQ. It specifies the exact resource and action, and is distinct from sibling tools like getPollenCount or getUvIndex.

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

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

The description implies the tool is for retrieving air quality data for a specific location, but offers no guidance on when to use it versus alternatives (e.g., getPollenCount) or when not to use it. No exclusions or context 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?

No annotations are provided, so the description carries the full burden. It mentions using Clearbit and HTML parsing but does not disclose limitations, data freshness, rate limits, or failure modes. The behavioral transparency is minimal.

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, concise sentence with no wasted words. It efficiently communicates the tool's core functionality and method.

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 simplicity (1 param, no output schema), the description is adequate but not complete. It explains what it does and how, but lacks details on error handling, return format, or constraints (e.g., does it only work for businesses?). The absence of annotations and output schema leaves 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?

Only one parameter 'domain' with no description in schema (0% coverage). The description adds context by saying 'public business URL', clarifying it expects a domain rather than a full URL. However, it does not explain the format or edge cases, so it adds some value but not enough for a higher score.

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 extracts brand logos and theme colors from a public business URL using Clearbit and HTML parsing. The verb 'extracts' and the resource 'brand logos and theme colors' are specific, and it distinguishes itself from sibling tools that perform other data retrievals.

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

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

The description provides no guidance on when to use this tool versus alternatives. It says 'for any public business URL' but does not mention exclusions, prerequisites, or compare to related tools like lookupCompany. Usage context is implied but not explicit.

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

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

With no annotations provided, the description discloses the fallback behavior (Blockscout) and the verification requirement. However, it fails to mention what happens for unverified contracts, error responses, or any other behavioral traits like authentication needs 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?

The description is exceptionally concise with two front-loaded sentences. The first sentence captures the main functionality and fallback, and the second lists matching use cases. No unnecessary words are present.

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

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

The tool lacks an output schema, so the description should explain the return format or structure, which it does not. Additionally, failure modes (e.g., unverified contracts) are not discussed, leaving the agent without critical information 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?

The input schema has 100% coverage, clearly describing both parameters (chain with enum/default and address with examples). The description adds no additional meaning beyond what the schema already provides, meeting the baseline score.

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 resolves contract ABI for Sourcify-verified smart contracts on Base or Ethereum, with a Blockscout fallback. It also lists matching use cases, helping to distinguish from potential similar tools, though no direct sibling names are mentioned.

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

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

The description implies usage for retrieving ABIs of verified contracts on specific chains, but does not explicitly state when to use or not use alternatives. The 'Matches' list provides context for applicable scenarios, but exclusions or prerequisite conditions are absent.

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

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

No annotations are provided, so the description shoulders full responsibility for behavioral disclosure. It mentions using Open Charge Map but fails to state if the tool is read-only, requires authentication, has rate limits, or any side effects. This is insufficient for a third-party data lookup 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?

The description is a single 12-word sentence that is directly front-loaded with the action and resource. Every word earns its place, with no redundancy.

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

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

Given no output schema, no annotations, and only 33% parameter coverage, the description is too sparse. It does not explain return values, error handling, or any constraints, leaving the agent with significant gaps for a 3-parameter 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 33% (only radius_miles has a description). The tool description adds no specific parameter meaning beyond the generic 'within a given radius,' leaving lat and lng unexplained. It does not compensate for the low coverage.

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 locates public EV charging stations within a radius using Open Charge Map. The verb 'locates' and resource 'public electric vehicle charging stations' are specific, and the tool is distinct from its siblings, which cover other 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 description implies usage for finding nearby EV chargers but provides no explicit guidance on when to use vs alternatives, nor any exclusions. The tool name and sibling context make its purpose clear, but guidelines are minimal.

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

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

No annotations are provided, so the description carries the full burden. It states the data source (FAA public API) and scope (US airports), but does not disclose behavioral traits like real-time nature, rate limits, or response structure. It is adequate but not rich.

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 sentence followed by a bullet list of matches. It is concise, front-loaded, and contains no unnecessary words. Every sentence contributes to understanding.

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 query tool with one parameter and no output schema, the description is fairly complete. It specifies the domain (US airport delays) and what data is returned (delays, ground stops, weather statuses). However, it lacks details on output format or structure, which would be helpful given no output schema.

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

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

Schema coverage is 100%, with a single parameter 'airport_code' well-described in the schema (pattern, examples). The description adds 'for a US airport' which is redundant but clarifies geographic scope. Overall, the description adds minimal 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 identifies the tool's purpose: querying the FAA public API for active delays, ground stops, and weather statuses for a US airport. It lists specific matching categories, making it distinct from siblings like getAirportBoard.

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

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

The description provides no guidance on when to use this tool versus alternatives (e.g., getAirportBoard or other delay-related tools in the sibling list). It does not mention when not to use it or any 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 the description carries full burden. It clearly states the tool retrieves data, implying a read-only, non-destructive operation. No hidden side effects or permissions are indicated, but the description is sufficiently transparent for a simple retrieval tool. A score of 5 would require explicit mention of rate limits or update frequency.

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 sentence that contains all necessary information: action, data retrieved, and source. No filler or redundant text. It is appropriately sized for the tool's simplicity.

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 no parameters and no output schema (so no return value explanation expected), the description is complete enough. It names the two rates and the data sources. A minor gap: it does not specify that the rates are latest (implied by 'latest effective'), which is fine. Score 5 would require explicit mention of update frequency or format.

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

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

The input schema has zero parameters (empty object), so there is nothing to describe. Baseline is high since no parameter documentation is needed. The description accurately reflects that no parameters are 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?

The description clearly states the tool retrieves two specific rates (effective federal funds rate and primary-credit rate) from named authoritative sources (New York Fed and H.15). It uses a specific verb ('Retrieves') and identifies the exact data, distinguishing it from sibling tools like getFundingRates which deal with different financial rates.

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 guidance on when to use this tool versus alternatives. While the description makes the tool's purpose clear, it does not mention when not to use it or name sibling alternatives for comparison. However, the context of sibling tools (e.g., getFundingRates, getMarketHalts) implies this is for federal reserve rates, but no direct exclusions.

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 full burden. It states 'queries live funding rates,' clearly implying a read-only operation with no destructive behavior. No contradictions or omissions about mutation.

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: the first explains core functionality, the second lists alternative search terms. No wasted words, though the second sentence could be considered extraneous.

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 tool with one optional parameter and no output schema, the description provides core purpose but does not explain the return format. An agent would benefit from knowing what fields are returned in an arbitrage opportunity.

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

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

Schema coverage is 100% with a single parameter min_funding_rate already described in schema. The description adds minimal context ('absolute' and 'percentage') but does not significantly expand beyond schema defaults.

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 queries live funding rates and mark-index spreads to locate yield arbitrage opportunities, using specific verbs and resources. It distinguishes from siblings like getFundingRates by focusing on arbitrage detection, and lists matching search terms for clarity.

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

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

The description does not provide explicit guidance on when to use this tool versus alternatives. It only lists related search terms, missing context about when to choose this over getFundingRates or other siblings.

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 full burden. It mentions 'active' gauges and 'potential' flooding, but does not disclose return format, side effects, permissions, or operational details like rate limits. Agents cannot know what to expect from the output.

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 sentence with a list of keywords, which is concise and front-loaded. The keywords are somewhat redundant but do not detract significantly. No wasted words, but could be more efficient by removing the list.

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 simplicity (one input, no output schema), the description falls short. It fails to indicate what the tool returns (e.g., list of flood warnings, severity levels). An agent lacks crucial information to interpret the tool's response.

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 parameter 'state', which already includes a description and example. The description adds the context of US states but does not enhance meaning beyond what the schema provides. Baseline score of 3 is appropriate.

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

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

The description clearly states the tool scans USGS gauge heights for potential river flooding, with a specific verb and resource. It includes keywords that help identify use cases. However, it does not explicitly differentiate from sibling tools like getWaterStreamflow, which also deals with water flow data.

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 is provided on when to use this tool versus alternatives. The description lacks context about prerequisites, such as requiring a valid US state code, or when not to use it (e.g., for non-flood related streamflow queries).

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 full responsibility for behavioral disclosure. It indicates a read operation ('queries') but lacks details on authentication, rate limits, or error handling. Adequate for a simple query tool but not comprehensive.

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 well-structured sentence, front-loading the verb and resource. Every word adds value; no 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 tool with one parameter and no output schema, the description adequately covers the purpose and parameter. It could be more explicit about what the tool returns, but overall it is 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% with description and examples for the single parameter. The description adds the context that the parameter is a 'contract ticker symbol' and that the tool is for perpetual swap contracts, adding 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 action (queries), specific resource (current pricing and funding rate margins), and the source (Binance perpetual swap contracts). It is specific and distinguishes from sibling tools that query other data types.

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

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

The description implies the tool is for obtaining Binance perpetual swap funding rates, but provides no explicit guidance on when to use it vs alternatives, nor when not to use it. Usage context is implied but not stated.

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

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

No annotations are provided, so the description carries full burden. It correctly indicates a read-like scanning operation, but does not disclose whether it is read-only, requires authentication, or has any side effects. The description is adequate but not comprehensive.

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, concise sentence that efficiently conveys the tool's purpose. It is front-loaded with the action and avoids unnecessary words. However, it could be slightly more structured (e.g., listing outputs explicitly).

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 one-parameter tool without output schema, the description covers the main functionality adequately. However, it lacks details about return format (e.g., units like gwei) and any prerequisites. It is minimally 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 description coverage is 100% for the single parameter 'blocks', which already provides a clear description and default value. The tool description adds no additional meaning beyond the schema, so baseline score of 3 is appropriate.

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

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

The description clearly states the tool scans recent block gas details to estimate minimum, average, and maximum base fee. It uses a specific verb ('scans') and resource ('recent block gas details'), and clearly differentiates from the many unrelated sibling tools (e.g., DNS, weather, finance).

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

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

The description implies the tool is for estimating gas fees, but it does not explicitly state when to use it (e.g., before submitting a transaction) or when not to use it. No alternatives are mentioned, though sibling tools are mostly unrelated. Usage context 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?

No annotations provided; description only implies a safe read operation without detailing any behavioral traits like rate limits, data freshness, or side effects.

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?

Single sentence, direct and front-loaded with the primary action. No wasted words.

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

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

Missing output schema and minimal description; does not explain return format, pagination, or any limitations. Incomplete for a tool with two required params and no annotations.

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

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

Schema coverage is 0%, and the description does not explain the purpose of 'year' or 'country_code' parameters, leaving the agent without critical usage details.

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

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

The description clearly states the tool retrieves holidays for business day verification across many countries, distinguishing it from sibling tools which cover different 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?

No guidance on when to use this tool versus alternatives or what prerequisites exist. With many sibling tools, lack of usage context reduces effectiveness.

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 should disclose behavioral traits. It only says 'queries,' implying a read-only operation, but lacks details on rate limits, data freshness, or any side effects. No contradictions but insufficient transparency.

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

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

The description is a single sentence, which is concise, but it could be slightly expanded to include key details without being verbose. It earns its place but leaves room for improvement.

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 simplicity of the tool (two numeric params, no output schema), the description is incomplete. It does not mention return format, units, or any constraints like valid coordinate ranges.

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 0%, and the description adds no meaning beyond the parameter names. It does not explain coordinate format, bounds, or the meaning of 'hourly lightning potential indices.' The description fails to compensate for the schema 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 clearly states that the tool queries hourly lightning potential indices for given coordinates. It uses a specific verb and resource, distinguishing it from sibling tools like getAirQuality or getUvIndex.

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 does not mention prerequisites, context, or situations where this tool is preferred.

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

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

Without annotations, the description must disclose behavioral traits. It mentions 'live observation data' but does not clarify data freshness, rate limits, authentication needs, or error 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?

Single sentence, no redundant information, front-loaded with the verb and resource.

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 annotations, the description is too minimal. It does not describe return format, example usage, or limitations. For a simple tool, it may partially suffice but lacks completeness.

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

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

Schema coverage is 100% with a description for buoy_id. The tool description adds context about the resource but does not enhance parameter meaning 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 action (Fetches) and resource (live observation data for a specific NOAA marine buoy station). It is distinct from sibling tools which cover other 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?

No guidance on when to use this tool versus alternatives. The description does not provide any prerequisites or exclusions.

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

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

No annotations are provided, so the description carries the full burden. It only states it parses an RSS feed but does not disclose potential errors, rate limits, data freshness, or whether authentication is needed. The behavioral profile is minimal.

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: a single sentence that is front-loaded with the action. No extraneous words or repetition, making it efficient for an AI agent to parse.

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 parameterless tool with no output schema and no annotations, the description is minimal. It explains the source and action but omits return format, example data, or any caveats. Sufficient but not thorough.

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

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

There are zero parameters and schema description coverage is 100%, meeting the high coverage threshold. The description adds no parameter info, but none is needed. Baseline 3 is appropriate.

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

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

The description provides a specific verb ('parses') and resource ('Nasdaq Trader RSS feed for active or recent stock trading halts'), clearly differentiating it from sibling tools that cover unrelated domains like air quality, DNS, or trademarks.

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, such as other financial data tools or when halts might be unavailable. The description simply states what it does without 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?

No annotations are provided, so the description carries full burden. It discloses the two modes but omits details on rate limits, error handling, or data structure of the result. Adequate but not thorough.

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, well-structured sentence with no wasted words. It efficiently conveys the core functionality.

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

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

The tool has no output schema, so the description should explain what the returned grant metadata contains. It does not, leaving the agent without guidance on expected output structure or content.

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 single parameter 'patent_number' is fully documented in the schema with an example and description. The tool description adds no extra semantic value beyond what the schema provides, meeting the baseline for high schema coverage.

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 queries Google Patents for grant metadata, with optional richer data via PatentsView Search API. This specifies the verb and resource, and while no sibling patent tools exist, it sufficiently differentiates from other get* 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 explains two usage modes: without a key for basic queries and with PATENTSVIEW_API_KEY for richer data. This provides clear context on when each mode applies, though it lacks explicit exclusions or alternatives.

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

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

Description implies a read-only query with no side effects, which is appropriate. However, with no annotations, it doesn't mention aspects like data freshness, rate limits, or whether results are real-time or historical.

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?

Single, front-loaded sentence with no wasted words. Efficiently conveys the tool's 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?

No output schema exists, and the description does not hint at the return format (e.g., numeric indices per pollen type, units, or structure). An agent cannot predict what the response will contain.

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%, and the description only says 'by coordinate' without explaining lat/lng range, format, or units. It fails to add meaningful semantics beyond the schema's parameter names.

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 queries pollen allergen index counts for specific types (grass, birch, oak) by coordinate, using a named service (Open-Meteo). This verb+resource+scope clearly distinguishes it from sibling tools like getAirQuality or getUvIndex.

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 guidance on when to use this tool versus alternatives (e.g., for other pollen types or when to prefer getAirQuality). Usage is only implied by the purpose 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?

No annotations are provided, so the description carries full burden. It states the data is 'live' and 'public', but does not disclose any behavioral traits such as rate limits, authentication requirements, or side effects. The read-only nature is implied but not explicit.

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, front-loaded sentence that conveys the core purpose without any extraneous information. 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?

Given the tool has one optional parameter, no output schema, and no annotations, the description provides minimal context. It lacks details on what the output looks like, behavior when market_id is omitted, and any other important usage nuances.

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 description does not add substantive meaning beyond the schema's own description of the optional market_id parameter. Baseline score of 3 is appropriate as the schema already documents the parameter adequately.

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 verb 'Retrieves', the specific resource 'live public prediction-market prices and contract odds', and the source 'Polymarket's Gamma data API'. It effectively distinguishes from sibling tools, none of which explicitly target prediction markets.

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

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

The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites, appropriate contexts, or which scenarios are better served by 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 are provided, so the description bears full responsibility for behavioral disclosure. It only mentions 'resolves direct streaming URLs' without explaining the output format, error handling, rate limits, or whether it returns a single URL or multiple. This is insufficient for safe and correct invocation.

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, front-loaded sentence that efficiently conveys the core purpose. It is concise with no filler, though breaking it into two sentences could improve readability.

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 lack of output schema and annotations, the description is incomplete. It does not specify the return format (e.g., array of objects, direct URLs), error scenarios, or the number of results. The tool's interface is not fully characterized, leaving the agent uncertain about how to interpret the output.

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 add semantic meaning. It mentions filtering 'by country or tag' which loosely maps to the parameters 'country' and 'genre', but does not elaborate on valid values, format constraints, or how the 'tag' relates to 'genre'. The schema examples are basic and not contextualized.

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 verb 'resolves', the resource 'direct streaming URLs', and the source 'open-source radio station database' with filtering criteria 'by country or tag'. It distinguishes from siblings as no other sibling tool appears to handle radio streaming.

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

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

The description does not explicitly state when to use this tool versus alternatives. There is no mention of context, prerequisites, or exclusions. The agent receives no guidance on when not to use it or what other tools might be more suitable.

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

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

No annotations are provided, so the description carries the full burden. It mentions the data source (transport.opendata.ch) but does not disclose rate limits, data freshness, authentication needs, or any limitations. For a live data tool, more behavioral details would be helpful.

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 concise sentence with no wasted words. It efficiently communicates the tool's purpose and scope.

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 simplicity of the tool (one parameter, no output schema, no annotations), the description is minimally adequate but lacks information about output format, pagination, or edge cases. Slightly more detail would improve completeness.

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

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

The input schema has 100% coverage with an example and description for the single required parameter 'station'. The description does not add meaning beyond the schema, so baseline score is appropriate.

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

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

The description clearly states the tool queries live train departures and schedule delays for European transit hubs, specifying the data source (transport.opendata.ch). This distinguishes it from siblings like getFaaDelays (airport delays) and getTransitStatus (broader transit).

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 use for European train updates but does not explicitly state when to use this tool versus alternatives like getTransitStatus or getFaaDelays. No when-not or alternative 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 must disclose behavioral traits. It only states that it queries an external API, but lacks details such as rate limits, whether it is read-only, how many results are returned, or if it requires authentication. For a tool hitting an external service, this is insufficient for an agent to gauge impact or reliability.

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 sentence that is front-loaded with the core action and resource. It contains no filler or redundant information, making it efficient for an agent to parse quickly.

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

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

The tool has no output schema, so the description should explain what the return value contains (e.g., list of earthquakes with location, time, magnitude). It only describes the input query, leaving the agent unaware of the response structure. For a simple tool, this gap reduces completeness.

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

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

Schema coverage is 100% as the single parameter 'min_magnitude' has a description in the schema. The tool description does not add extra meaning beyond the schema (e.g., valid range, examples, or units). Baseline 3 applies, but no additional value is provided.

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 queries the USGS Earthquake Hazards API for recent earthquakes with a minimum magnitude. It specifies the resource ('earthquakes'), action ('queries'), and scope ('recent', 'exceeding a minimum magnitude'), distinguishing it from sibling tools like 'getAirportBoard' or 'getFaaDelays' which target different data.

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 is provided on when to use this tool versus alternatives. There is no mention of scenarios where this tool is appropriate or when to avoid it, nor any comparison with sibling tools. A usage-optimal description would include context like 'Use for filtered earthquake data; for all earthquakes, consider alternative endpoints.'

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. Description mentions 'public OSRM engine' implying free usage but no details on rate limits, data freshness, or reliability. Also 'shortest driving distance' clarifies it's not fastest or alternative routes. Minimal behavioral disclosure.

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

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

Single sentence is concise but lacks essential details. No wasted words, but conciseness comes at the cost of completeness. Could be restructured to add parameter notes or output format without becoming verbose.

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. Description does not specify return format (e.g., distance in km/miles, duration in seconds/minutes, whether it returns a JSON object with keys). For a tool with 4 required parameters and no schema descriptions, completeness is severely lacking.

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 0% for descriptions. The description does not explain the parameters (start_lat, start_lng, end_lat, end_lng) beyond their names. No units, constraints, or formatting details. With no schema descriptions, the description should compensate but fails to do so.

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 computes shortest driving distance and duration between two coordinates using OSRM. Specific verb 'computes' and resource 'distance and duration' are described. No explicit sibling differentiation, but given the diverse sibling list, it's reasonably clear.

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. No mention of prerequisites (e.g., coordinate format, limitations of OSRM engine, rate limits). Agent is left to infer usage context from the 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?

The description mentions using Ziptax and Zippopotam for enrichment, but does not disclose data freshness, accuracy, limitations, or output format. Since no annotations are provided, the description carries full burden and fails to provide sufficient behavioral detail.

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

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

The description is concise: two sentences followed by a list of use cases. It is front-loaded with the core purpose and avoids unnecessary words.

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

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

The description explains what the tool does and lists use cases, which is adequate for a simple tool with one parameter. However, it lacks details about output format and error handling, leaving some 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 100% with a single parameter 'zip_code' described as '5-digit US ZIP code'. The description does not add additional meaning beyond the schema, so baseline 3 is appropriate.

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

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

The description clearly states the verb 'locates', the resource 'combined sales tax rate (state, county, local)', and the scope 'for a US ZIP code'. It also lists matching use cases. The tool is distinct from sibling tools which are unrelated.

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

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

The description provides a list of matching use cases (sales tax rate calculator, zip code tax lookup, etc.), which gives clear context for when to use. However, it does not explicitly state when not to use or name alternative tools, but sibling tools are unrelated, so no exclusions are needed.

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 states 'retrieves' implying a read-only operation, but does not disclose details like data freshness, caching, or any side effects. Adequate but minimal.

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 extremely concise with two sentences: the first states the action, the second provides search keywords. No wasted words, front-loaded with the main 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 parameterless tool with no output schema, the description is largely complete. It could mention data source freshness, but that is a minor gap.

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?

No parameters exist, so schema coverage is 100%. The description adds no param info, but baseline for zero params is 4, as no additional meaning is needed.

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

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

The description clearly states the tool retrieves the current planetary K-Index and active solar storms from NOAA SWPC, using a specific verb and resource. It also provides matching keywords that distinguish it from sibling tools like getWeatherAnomaly or getAirQuality.

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

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

The description implies usage for solar weather data but provides no explicit guidance on when to use this tool versus alternatives, nor does it mention any prerequisites or conditions.

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 must fully disclose behavioral traits. It mentions 'live' and 'active USGS gauges' implying real-time data, but omits details like rate limits, error handling for states without gauges, or read-only nature.

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 concise sentence that is front-loaded with the verb and resource. Slightly more structure (e.g., mentioning output format) would improve it.

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 one-parameter query tool with no output schema, the description covers the core function adequately. However, it lacks behavioral details like data freshness constraints or potential missing data handling.

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 the state parameter fully described. The description adds no extra meaning beyond the schema, so baseline 3 is appropriate.

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

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

The description clearly states the verb 'Queries' and the specific resource 'live stream water temperature telemetry from active USGS gauges in a US state', distinguishing it from siblings like getWaterStreamflow and getMarineConditions.

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

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

The description provides no guidance on when to use this tool versus alternatives, such as getWaterStreamflow for flow data or getMarineConditions for marine environments. It lacks explicit or implicit usage 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 fully explains the tool's behavior: scanning bytecode, checking ownership renouncement, and cross-referencing DexScreener for liquidity. It discloses that it returns a risk score and flags, providing good transparency without contradictions.

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 sentence that efficiently conveys the tool's bundling of checks and output. While dense, it is well-structured and includes search keywords. Minor improvement could be shorter sentences for readability.

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

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

The description mentions returning a risk score with flags but lacks detail on the output structure (e.g., score range, flag meanings). With no output schema, this gap affects completeness for a tool performing complex checks.

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 single parameter 'address' is fully described in the schema (100% coverage) as an ERC-20 token contract address on Base. The description adds that the tool is for 'untrusted' tokens, but this is contextual rather than adding parameter semantics. Baseline 3 is appropriate.

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

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

Description clearly states the tool bundles checks for trusting an unfamiliar ERC-20 token, listing specific scans and returning a risk score. The matching keywords further clarify the purpose. It distinguishes from siblings like getContractAbi by focusing on safety assessment.

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 evaluating token safety ('before trusting an unfamiliar ERC-20 token') and provides matching query phrases. However, it does not explicitly state when not to use or mention alternative tools like getContractAbi.

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 must disclose behaviors. It notes reliance on Google Routes, requiring an API key, and that distance inputs are non-authoritative. However, it fails to mention whether the tool is read-only, rate limits, error handling, or authentication details beyond the key.

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 only two sentences with no redundancy. The first sentence states purpose and prerequisites; the second adds a crucial limitation. 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?

The description covers the primary function and a key caveat, but lacks information about return values (format, currency, time), failure scenarios (e.g., missing API key), and dependencies like internet connectivity. Given no output schema, more detail is warranted.

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 descriptions already explain origin/destination as coordinates or addresses and vehicle_type as optional. The description adds no new semantic meaning beyond what the schema provides, meeting the baseline.

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 calculates route toll estimates via Google Routes, specifying inputs (origin/destination coordinates or addresses) and a required API key. It also distinguishes from state-only distance inputs, making the purpose 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?

The description implies usage for toll estimates requiring an API key, but does not explicitly state when to use this tool over siblings like getRouteDuration, nor does it provide when-not-to-use guidance. The caveat about state-only distances provides some context but lacks alternative suggestions.

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

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

No annotations are provided, so the description carries the full burden. It discloses the data source (official MTA GTFS-RT feed) and mentions the ability to request other cities, which is a notable behavioral detail. However, it does not disclose data freshness, rate limits, authentication needs, or error handling for invalid cities/lines.

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

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

The description is two sentences long, with the first sentence front-loading the core functionality. Every word adds value, and there is no redundancy or fluff.

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

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

The tool has no output schema, so the description should explain what information is returned beyond 'alerts, delays, planned-work advisories.' It lacks details on data format, verbosity, pagination, or how to interpret results. Given the low schema coverage and absence of annotations, the description is insufficient for an agent to fully understand the tool's capabilities.

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

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

The input schema has 0% description coverage, so the description must add meaning. It implicitly explains 'city' (NYC or other cities via request) and 'line' (subway line), but it does not specify accepted values, formats, or how to request other cities (e.g., what city values to use). The examples in the schema are minimal, and the description adds only vague context.

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 subway alerts, delays, and planned-work advisories' from the official MTA GTFS-RT feed, which is a specific verb ('get') and resource ('transit status'). It distinguishes itself from siblings like getFaaDelays, getAirportBoard, and getRailStatus by being subway-specific and NYC-oriented.

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 specifies that the tool is for NYC lines and mentions that other cities can be requested via an endpoint. However, it does not provide explicit guidance on when to use it versus alternatives like getRailStatus, nor does it state prerequisites or exclusions (e.g., not for buses).

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, and the description omits behavioral details such as data source, update frequency, or what 'sun safety burn times' entails, leaving the agent with limited understanding.

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?

Single sentence, directly states purpose, no extraneous words.

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

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

No output schema, no annotations, and minimal description fail to convey the return value structure or any constraints, leaving significant gaps 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?

With 0% schema description coverage, the description adds no meaning to the lat/lng parameters; it doesn't explain their format (e.g., decimal degrees) or acceptable ranges.

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 specific resource ('solar UV Index') and action ('retrieves' and 'calculates'), distinguishing it from sibling climate tools like getAirQuality or getPollenCount.

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; no context on prerequisites or when not to use it.

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 must disclose behavioral traits. It does not mention that the operation is read-only, safe, or idempotent. For a read-only tool, this is a significant gap, leaving the agent uncertain about side effects.

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, concise sentence with no unnecessary words or repetition. It is front-loaded with the key action and resource.

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

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

The tool is simple, but without an output schema, the description should clarify what the output contains (e.g., separate native and token balances, format). It lacks this detail, leaving the agent to infer the 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?

The input schema has 100% description coverage for both parameters. The description adds high-level context (scans native and ERC-20) but does not enrich parameter-specific details beyond what the schema already provides.

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

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

The description clearly states it scans native and ERC-20 balances for a wallet on Base or Ethereum, using a specific verb and resource. It distinguishes itself from sibling tools like getTokenSafety or getGasHistory, which serve different purposes.

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

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

The description specifies the context (wallet balances on Base or Ethereum) but does not explicitly state when not to use it or mention alternatives. The context is clear enough for an agent to infer usage.

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?

Annotations are absent, so the description must fully disclose behavioral traits. It states 'live' but omits rate limits, data freshness, precision, or any limitations of the USGS streamflow data. Minimal transparency beyond basic functionality.

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?

Single sentence of 20 words, front-loaded with the action. No wasted words; every part contributes to understanding the tool's 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 simple tool with one parameter and no output schema, the description covers basic purpose but lacks details on output format, usage notes, or limitations. Adequate but with 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?

The description adds no meaning to the single 'state' parameter beyond the schema, which already provides type and example. Schema coverage is 0%, so the description should compensate but fails to clarify format (e.g., two-letter code) or that it's 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?

The description clearly states the verb 'queries', the resource ('live US river level, streamflow gauge height, and flow velocity metrics'), and the data source ('USGS National Water Information System'). It effectively distinguishes this tool from related hydrology tools like getFloodWarnings or getStreamTemperature.

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 is provided on when to use this tool versus alternatives such as getFloodWarnings or getStreamTemperature. There is no mention of prerequisites, context, or when not to use it.

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 explains the comparison and flagging, but does not disclose what 'flagging' means (e.g., return format, severity), data source, or refresh rate. Minimal transparency.

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

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

Single sentence, no fluff. However, it could be restructured to include parameter or output hints without becoming verbose.

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 or annotations. The description lacks details on output format, error conditions, or data source. Incomplete for a tool with moderate complexity.

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

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

Schema coverage is 0% (no parameter descriptions), and the description does not mention lat/lng or their relevance. It only describes the overall function without linking to input parameters.

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

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

The description clearly states the tool compares current weather with a 10-year historical average to flag climate anomalies. It uses a specific verb ('compares') and resource ('weather conditions'), and distinguishes well from weather-related sibling tools like getAirQuality or getLightningPotential.

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 description does not mention prerequisites, exclusions, or context where this tool is preferred over similar 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 provided; description covers the read-only nature ('scans') and data source but omits details like authentication, rate limits, or error handling. Acceptable for a simple data fetch.

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 includes a list of keywords ('Matches:') that add little value for an AI agent. Could be more concise and focused on 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?

No output schema exists, and the description only hints at 'latest reported geometry' without detailing return structure. For a simple tool with one parameter, this is minimally adequate.

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 fully describes the 'state' parameter, but the description adds no further context. The optional nature or default behavior is not clarified, leaving the agent to infer scope.

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 scans NASA EONET for currently open wildfire incidents and their geometry. This verb+resource combination uniquely identifies the tool's function among siblings like getRecentEarthquakes and getAirQuality.

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 real-time wildfire data retrieval but does not explicitly state when to use it vs alternatives. No mention of prerequisites or context for state parameter.

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

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

With no annotations provided, the description carries full burden. It does not disclose rate limits, data freshness, handling of invalid barcodes, or any behavioral traits beyond resolving metadata from free endpoints.

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, clear sentence with no redundant information. Every part is useful, making it highly concise and well-structured.

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

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

For a simple tool with one parameter and no output schema, the description is adequate but lacks specifics about what 'detailed product metadata' includes, error handling, or usage limitations. Additional details would improve completeness.

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

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

Schema coverage is 100% with a single barcode parameter. The description adds context about using OpenLibrary and UPCitemdb but does not enrich the parameter beyond the schema's description and examples. Baseline 3 is appropriate.

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

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

The description clearly states the tool resolves UPC/EAN/ISBN barcodes into detailed product metadata using specific endpoints. It uses a specific verb and resource, and is distinct from sibling tools like lookupCompany or lookupIp.

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

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

The description implies usage for barcode resolution but does not explicitly mention when not to use it or provide alternatives. It names the data sources but lacks guidance on context or exclusions.

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, and description does not disclose behavioral traits like data freshness, rate limits, authentication, or error handling. The tool's side effects or restrictions are not mentioned.

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?

Description is three sentences, front-loaded with purpose and outputs. No extraneous 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?

Lists retrieved data but does not explain return structure, error behavior, or any special requirements. Adequate for a simple tool but could be more complete given no output schema.

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

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

Schema coverage is 100% with a good description. The tool description adds no extra parameter insight beyond the schema's 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?

Description clearly states it searches SEC EDGAR for US public companies and lists specific outputs (address, SIC, ticker). It distinguishes from sibling lookup tools by domain (SEC vs barcode, IP, etc.).

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?

Description explicitly targets US public/SEC-registered companies, implying use case. But lacks explicit when-not-to or alternatives (though siblings cover other domains).

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 full burden. It discloses use of public geodata and the types of resolved data (location, country, ISP, AS, hosting flags). It doesn't mention destructive behavior (none expected), rate limits, or permissions, but for a lookup tool this is sufficient.

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

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

The description is two sentences with a bullet list, front-loading the core action in the first sentence. It is concise without extraneous words.

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

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

The description covers the input (IP address) and output components (location, country, ISP, AS, hosting flags). With only one param and no output schema, it provides adequate completeness for a geolocation lookup tool.

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

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

Schema coverage is 100%, and the description adds 'IPv4 or IPv6 address to geolocate', which is already in the schema's property description. Thus the description adds no new meaning beyond the schema, warranting a baseline score of 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?

The description clearly states the tool scans an IP address using public geodata to resolve location, country, ISP, autonomous system, and hosting flags. The list of matches further reinforces specific use cases, and the tool is well-differentiated from siblings like auditDnsSecurity or checkDnsPropagation.

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 'Matches:' list provides explicit usage scenarios (e.g., geolocate IP address, check client IP country, query ISP metadata). While it doesn't mention when not to use or alternatives, the matches offer clear guidance. Sibling tools cover different domains, so differentiation is implicit.

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 must cover behavior. It states that the tool queries the global RDAP bootstrap directory, implying a read operation. However, it does not mention rate limits, authentication needs, or side effects. Given the simplicity, this is adequate but not rich.

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 convey the purpose and key return fields. No extraneous information. Front-loaded with the core action.

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 single-parameter lookup tool with no annotations or output schema, the description sufficiently explains what it does and what it returns. It is complete and actionable.

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 covers 100% of parameters (domain) with an example. The description adds value by listing the kind of data returned (registrar, creation date, expiration), which clarifies the tool's output 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 specifies that the tool queries the RDAP bootstrap directory for domain registration details, including registrar, creation date, and expiration. It also lists matching search terms, making the purpose evident and distinct from siblings like lookupIp or lookupCompany.

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

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

The description provides matching search terms but does not explicitly state when to use this tool over alternatives. For a tool with many siblings, more explicit usage guidance would improve selection accuracy.

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?

Given no annotations, the description discloses key behaviors: paying gas on behalf, charging USDC via EIP-3009 receiveWithAuthorization. It mentions the method and parameters, but could be more explicit about success/failure responses (e.g., transaction hash).

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: one sentence plus a matching line. It is front-loaded, no wasted words, and effectively communicates the core function.

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

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

The tool has 7 required parameters and no output schema. The description explains the overall mechanism but omits details about return values (likely transaction hash) and potential failure states, which would help an agent confirm success.

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

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

Schema coverage is 100%, so baseline is 3. The description adds context about EIP-3009 but does not significantly enhance parameter understanding beyond the schema descriptions.

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

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

The description clearly states the tool relays a transaction to Base Mainnet, paying gas and charging USDC via EIP-3009. It provides specific verbs and resources, and the 'Matches:' line aids discovery, distinguishing it from siblings like simulateTransaction.

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

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

The description implies usage for gasless transaction relaying on Base Mainnet with USDC payment, but lacks explicit when-to-use or when-not-to-use guidance. No alternatives 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.

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

With no annotations, the description carries full burden. It reveals the triggering of a contract and the authorization requirement, but lacks details on side effects like gas costs, confirmation delays, revert conditions, or idempotency. This is adequate but not comprehensive for a transactional 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 sentences: the first states the core action, the second adds the authorization constraint and alternative search terms. No wasted words, front-loaded with the primary 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 tool with 2 parameters and no output schema, the description is nearly complete. It explains the action, constraint, and contract. It could briefly mention expected outcomes (e.g., 'returns a transaction hash'), but is sufficient for agent invocation.

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

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

The schema already describes both parameters (bounty_id as hex ID, worker_wallet as EVM address) with 100% coverage. The description adds minimal context beyond the schema (e.g., 'locked USDC bounty'), which is already implied in the schema description. Baseline 3 is appropriate.

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

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

The description clearly states the tool triggers a contract to release a locked USDC bounty to a worker wallet, specifying the exact verb (releases) and resource (EscrowRegistry contract). It distinguishes itself from siblings like depositCoordinationBounty by mentioning 'release' and 'locked bounty'.

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

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

The description explicitly mentions that only the StatePulse hot wallet can authorize the release, providing a clear prerequisite. However, it does not explicitly state when to use this tool versus alternatives (e.g., when not to use it or that depositCoordinationBounty is the counterpart for creating bounties).

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

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

No annotations are provided, so the description carries the full burden. It discloses that the endpoint is free, that requests are reviewed, and that frequently requested data becomes a real endpoint. However, it does not detail storage or privacy of requests, rate limits, or authentication needs. The description adds some behavioral context but could be more transparent about the request lifecycle.

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 somewhat long but efficiently packed with relevant information: free endpoint, usage context, process, and matches. It front-loads the key point 'FREE endpoint' and uses clear language. Every sentence contributes to understanding, though minor trimming could improve conciseness.

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 simple nature (a request form for data), the description is fairly complete. It explains purpose, process, outcome, and gives examples of when to use. There is no output schema, but the output is likely a simple confirmation, and the description suffices. The sibling tools are many, but this tool's distinct role is well-communicated.

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 covers all 6 parameters with descriptions (100% coverage), so the baseline is 3. The description adds minimal additional meaning beyond the schema; it reiterates the purpose of requesting data and provides match keywords, but these do not substantially clarify parameter usage beyond what the schema already provides.

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

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

The description clearly identifies the tool as a request endpoint for missing data, using specific language like 'needs live data this API does not serve yet' and listing examples (feed, metric, lookup, another city or chain). It distinguishes itself from the many sibling data retrieval tools by focusing on requesting new endpoints rather than using existing ones.

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 states when to use the tool ('If your agent needs live data this API does not serve yet') and hints at alternatives by advising to re-fetch openapi.json or llms.txt to see new endpoints. It does not explicitly say when not to use, but the context makes it clear that it is for missing data only, not for already available endpoints.

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 must disclose behavioral traits. It accurately states it is a simulation (read-only) via eth_call, but does not mention potential limitations, rate limits, or authentication. The core behavior is transparent, but more detail would help.

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?

Description is a single concise sentence followed by a bullet-point list of matching use cases. Every sentence adds value; no fluff. The core purpose is front-loaded.

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 4 parameters, no output schema, and no annotations, the description sufficiently explains the tool's purpose and provides a helpful list of use cases. It could mention the return value format (e.g., boolean for revert) but is otherwise 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?

All four parameters have descriptions in the input schema (100% coverage). The tool description does not add additional parameter-level semantics beyond the schema; it only lists use cases. With high schema coverage, baseline 3 is appropriate.

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

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

Description clearly states it runs eth_call state simulation against Base blockchain RPC to check for transaction reverts. The list of matching use cases (e.g., EVM revert checks, dry-run, gas estimator) further distinguishes it from unrelated sibling tools like relayTransaction.

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 implicitly tells when to use by listing matching scenarios (e.g., test contract call, simulate multisig). However, it does not explicitly mention when not to use or point to alternative tools (e.g., relayTransaction for actual sending), but the use case list 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?

The description discloses that feedback is reviewed and data-quality reports are fixed with priority, and that submitting improves future results. Since no annotations are provided, the description fully covers behavioral aspects without contradiction.

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, front-loaded with 'FREE endpoint', and uses bullet-like matches list. Every sentence provides value, with no wasted words.

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

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

Despite no output schema, the description explains the outcome (feedback reviewed and fixed) and the impact. For a simple 3-parameter tool, this is 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 description coverage is 100%, so baseline is 3. The description adds context like 'FREE endpoint' and examples, but does not provide additional meaning beyond what the schema already documents for each parameter.

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 is for reporting feedback about the API, with specific examples like wrong data, endpoint failures, pricing issues. It is distinct from sibling tools which are data retrieval or audit 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?

It explicitly mentions it's a free endpoint and lists matching scenarios (report wrong data, endpoint broken, etc.), providing clear context for when to use. However, it doesn't explicitly state when not to use it versus alternatives.

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

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

No annotations are provided, so the description must disclose all behavioral traits. It mentions this is a 'FREE endpoint' and that 'Feedback is used to optimize pricing decisions', but lacks details on side effects, permissions, or what happens after submission. This is insufficient for full transparency.

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

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

The description is two sentences long, front-loaded with the core purpose, and contains no unnecessary words. 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?

The tool has no output schema and no annotations, yet the description fails to mention what the agent should expect as a return value or confirmation. It also does not address error handling or required permissions. For a tool with 4 parameters, this is incomplete.

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 baseline is 3. The description adds context ('based on alternative sources, budget limitations, or query frequency') but does not map these to parameters or add meaning beyond the schema descriptions.

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

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

The description clearly states the verb 'suggest a target price' and the resource 'a paid endpoint's pricing'. It distinguishes itself from sibling tools which are mostly audit/check/get tools, making its purpose unique.

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

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

The description explicitly states when to use this tool: 'If a paid endpoint's pricing is too high'. It also signals it is a free endpoint. However, it does not mention alternatives or when not to use it, which prevents a perfect score.

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

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

No annotations are provided, so the description carries full behavioral disclosure burden. It mentions 'live' data but does not disclose rate limits, data freshness, or whether the tool requires authentication. The term 'airspace vectors' is left undefined.

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 sentence that efficiently communicates the tool's purpose and parameters. No redundant information is present, and the structure is optimal.

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 lack of annotations and output schema, the description adequately explains the tool's core function but omits details on output format, error handling, and potential limitations. It is sufficient for a simple query tool but not fully comprehensive.

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

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

The description names the two parameter categories (ICAO24 identifier and bounding box) but adds little beyond the schema, which already includes descriptions and examples for icao24 and nested bbox fields. With 50% schema coverage, the description provides marginal extra 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?

The description clearly states it queries live airspace vectors for an ICAO24 identifier or bounding box, using OpenSky Network. It distinguishes itself from sibling tools like trackMarineVessel, which query marine data, by specifying the airspace domain and the specific query modes.

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

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

The description does not provide explicit guidance on when to use this tool versus alternatives. It mentions the data source (OpenSky Network) but lacks context about prerequisites, when not to use it, or comparisons with similar tools like trackMarineVessel.

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 must fully disclose behavioral traits. It states the tool resolves data but does not clarify whether a WebSocket connection is opened (for AISStream), what persistence or rate limits exist, or whether authentication is needed. The term 'resolve' implies a query, but the fallback mechanism introduces potential statefulness that is not explained.

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 sentence that front-loads the core action and key data sources. It is concise and avoids redundancy. However, it could be slightly more structured by separating the primary data source from the fallback, but overall it is 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?

For a tool with one parameter, no output schema, and no annotations, the description covers the essential functionality. However, it omits details about response format, error handling (e.g., invalid MMSI), and the implications of the optional AISStream fallback. This leaves some uncertainty for the 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?

With 100% schema coverage, the schema already describes the mmsi parameter as a 9-digit MMSI number. The description merely reiterates 'by MMSI number' without adding syntactic or semantic details (e.g., validation rules, example formats). Thus, the description provides minimal added 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 identifies the tool's purpose: resolving current coordinate telemetry and voyage details for a cargo ship by MMSI. It specifies the data source (public VesselFinder) and an optional fallback (AISStream), making it distinct from sibling tools like trackAirspace or getMarineConditions.

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

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

The description does not explicitly state when to use this tool versus alternatives. It mentions an optional fallback but offers no guidance on when AISStream is appropriate or when other marine tools (e.g., getMarineConditions) should be preferred. This lack of usage context leaves the agent without clear decision 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 provided, but description discloses key behavioral aspects: validation involves physical route and latency offsets, output is a cryptographically signed certificate. Does not mention destructive effects 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 sentences front-load the main action, followed by keyword list. Slightly redundant but overall concise.

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?

Adequate for a 2-param tool with no output schema. Could describe the certificate format or give an example, but not missing critical 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 coverage is 100%, so description does not need to add param details. The description itself does not elaborate on parameters beyond what the schema provides.

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

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

Description clearly states the tool validates IP route and latency for country compliance, returning a signed certificate. It distinguishes from siblings like lookupIp by specifying the verification process.

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. The match keywords imply use cases but don't clarify when to prefer this over alternatives like lookupIp or checkTimezone.

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