toolvend

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

No annotations are provided, so the description carries the burden. It discloses the use of DoH and the output format (clean JSON), but does not mention rate limits, authentication requirements, or error behavior. The cost information is a positive addition, but overall behavioral detail is moderate.

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, consisting of two short sentences that convey the essential purpose, output format, and cost. No redundant information is present, and the key details 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?

Given the simplicity of the tool (two parameters, no output schema), the description is reasonably complete. However, it lacks details on the return JSON structure and error conditions, leaving some ambiguity for an agent invoking this 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 input schema already covers both parameters with descriptions (100% coverage). The description adds little semantic value beyond mentioning 'common record types', which the schema's enum already enumerates. Thus the description does not significantly enhance parameter understanding.

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

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

The description clearly states the tool performs DNS lookup over DoH, specifying it returns common record types as clean JSON. This is a specific verb-resource combination that distinguishes it from sibling tools like email-auth or rdap, 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 provides practical usage guidance by noting the cost ($0.005 per call via x402), which helps an agent decide when to use it. However, it lacks explicit when-not-to-use scenarios or alternatives, which would improve the score further.

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

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

With no annotations, the description carries the full burden. It discloses that the tool fetches records, parses, scores, and returns findings/recommendations, and also states the monetary cost. It does not mention rate limits or caching, but the read-only nature is clear.

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

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

The description is two sentences, front-loaded with the main purpose, and includes necessary detail without extraneous 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?

Given one parameter and no output schema, the description covers the tool's actions (fetch, parse, score, recommend) adequately. It could mention output format or error cases, but for this complexity it is mostly complete.

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

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

Schema coverage is 100% for the single parameter 'domain', and the description in the main text does not add additional meaning beyond the schema's description 'Domain to analyse (path parameter)'. 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 fetches DMARC and SPF records, parses them, scores 0-100, and provides findings and recommendations. The verb 'authentication posture' is specific and the resource 'domain' is clear. It distinguishes from sibling tools (e.g., dns, extract) by focusing on email security.

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 mentions a paid cost ($0.01 per call via x402), which is a usage condition but does not explicitly state when to use this tool vs alternatives or provide exclusions. The usage context is implied but not formally guided.

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

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

No annotations exist, so the description must cover behavior. It discloses pricing, JavaScript rendering, boilerplate stripping, and included content, but omits failure modes, rate limits, or auth requirements. 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 clear but slightly repetitive on pricing ('$0.01 ($0.03 Execute JavaScript...') and could be more concise. It front-loads the core purpose but contains some 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, and the description does not detail the return format or error handling. For a non-trivial extraction tool, this leaves significant gaps in 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%, baseline 3. The description adds value by explaining the render parameter's cost and purpose beyond the schema's enum, and clarifies the includeLinks default. This extra context justifies a 4.

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 specifies 'Fetch a web page and return structured content' with a clear list of extracted elements (title, meta, canonical, etc.), and the tool is distinct from all sibling tools (DNS, email-auth, etc.), 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 explicit guidance on when to use the render parameter ('for JavaScript-rendered pages') and mentions pricing; however, no guidance is given on when not to use it or alternatives, though siblings are unambiguously different.

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 carries the burden; it discloses payment requirement, data freshness, and checksum verification. It lacks details on rate limits or error handling, but is sufficient for a 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?

Two sentences front-load all key information: purpose, data returned, and pricing. Every sentence is essential.

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 lists categories returned (identity, jurisdiction, etc.), which is sufficient for an agent to understand the output. Missing structure details, but acceptable for a single-param lookup.

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 param 'lei', but description adds value by noting it's a path parameter, checksum verified before payment, and the 20-character pattern (though pattern is in 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 explicitly states it performs global legal-entity/KYB lookup by LEI, lists specific data fields (identity, jurisdiction, addresses, etc.), and distinguishes itself from sibling tools like dns, email-auth, 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?

The description mentions paid per call via x402, implying a cost-sensitive context, but does not provide explicit when-to-use or when-not-to-use guidance relative to 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 present, so the description bears full responsibility. It discloses the output format (SVG), pricing ($0.003 per call), and payload constraints (2048 bytes, error-correction trade-off). It does not mention authentication or rate limits, but these are common and not critical for a simple generator.

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. The first sentence states the core purpose and key constraints; the second adds essential pricing info. Perfectly front-loaded and efficient.

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

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

For a 3-parameter tool with full schema coverage and no output schema, the description sufficiently explains return format (SVG), constraints, and cost. It lacks error-handling details but is adequate for typical use.

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 covers 100% of parameters. The description adds value by explaining the interaction between data length and error-correction level (e.g., capacity lower at Q/H), which goes beyond the static schema descriptions. It also reinforces the output format.

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 is a QR code generator that returns an SVG for text/URL payloads, with explicit constraints (2048 bytes). No sibling tools serve a similar function, so differentiation is not needed.

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

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

While no explicit 'when-to-use vs alternatives' is provided, the context is clear: it generates QR codes. The description implies usage limits (payload size and error-correction capacity), but lacks exclusions or alternatives since none exist 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?

No annotations are provided, so the description bears full responsibility for behavioral disclosure. It reveals pricing per call and data returned, but does not mention rate limits, required permissions, or whether the tool is idempotent. The pricing disclosure is a positive behavioral trait.

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 listing key data and pricing, which is concise and to the point. It could be slightly more structured (e.g., separating purpose from pricing) but is efficient with no redundant 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?

For a simple lookup tool with one parameter and no output schema, the description covers purpose and pricing. However, it lacks mention of return format, error handling, or when to prefer RDAP over sibling tools like 'dns'. It is adequate but not 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?

Schema description coverage is 100% for the single parameter, which already describes 'domain' as a path parameter. The tool description adds no additional semantic meaning beyond listing data fields, so it meets the baseline but does not exceed 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?

The description clearly states the tool retrieves domain registration data via RDAP, listing specific data fields (registrar, dates, status, nameservers, DNSSEC). It distinctly differentiates from sibling tools like 'dns' by focusing on registration data rather than DNS records.

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. While pricing is mentioned, there is no description of optimal use cases, prerequisites, or comparative context with sibling tools like 'dns' or 'whois'.

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 the core behavior, optional inclusion of llms.txt, output format, and pricing. No annotations exist, so it carries the full burden. Missing details on error handling or response structure prevent a higher score.

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, both essential: one for the core function, one for pricing. No unnecessary words; front-loaded with the 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 tool without output schema or annotations, the description covers purpose, optional behavior, and cost. Lacks details on error handling or output structure, but remains usable for an AI agent.

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

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

Schema coverage is 100% with a description for 'url'. The tool description does not add new information about the parameter beyond what the schema already provides, so baseline applies.

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

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

The description clearly states the tool fetches and parses robots.txt (and optionally llms.txt) into structured JSON, specifying it includes which AI crawlers are blocked. This is distinct from sibling tools like sitemap or dns.

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 vs alternatives. The description implies it's for checking AI crawler blocking, but does not mention 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?

Discloses key behaviors: XML/gzip parsing, index following with ?follow=N, output cap at 500 URLs, and per-call pricing. No annotations present, so description carries the full burden adequately.

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

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

Three sentences with no waste: first sentence states core function, second covers index handling, third caps and pricing. Front-loaded and efficient.

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

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

Fairly complete given simplicity: covers purpose, usage, pricing, output cap. Minor omission of error handling or output format details, but sufficient for a straightforward tool with 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?

Adds significant value beyond the input schema by specifying URL formats (including .xml.gz and origin fallback) and explaining follow's role in index context. Schema coverage is 100% but description enriches understanding.

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

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

The description clearly states the verb 'Fetch and parse' and resource 'sitemap XML or gzip into JSON', and distinguishes from sibling tools which cover different domains (DNS, email, 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?

Provides clear context on how to use the tool (fetch sitemap, use follow for indexes, output cap, pricing) but does not explicitly mention when not to use 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?

No annotations are provided, so the description carries the full burden. It discloses pricing (paid per call), which is a behavioral trait. However, it does not mention authentication requirements, rate limits, or error handling. The description adds some value beyond the schema by stating the output includes stats.

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

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

The description is concise, consisting of two sentences. It front-loads the primary action: 'Clean text: ...' and then briefly mentions output and pricing. Every sentence provides useful information without 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?

No output schema is provided, so the description should clarify the return format. It states 'Returns cleaned text plus stats' but does not detail the structure of the stats. Additionally, there is no mention of error handling or edge cases. For a simple text-cleaning tool, this is adequate but not fully 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 50%. The description lists the operations (strip HTML, normalize unicode/whitespace, dedupe lines) which correspond to the boolean options in the schema, but does not elaborate on the 'options' parameter or 'text' parameter beyond what the schema provides. It adds marginal meaning but does not fully compensate for the lack of parameter documentation in the schema.

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

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

The description clearly states the tool's purpose: cleaning text by stripping HTML, normalizing unicode/whitespace, and deduplicating lines. It also mentions the output (cleaned text plus stats) and pricing. This distinguishes it from sibling tools which are network-related (dns, rdap, 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?

The description does not explicitly state when to use this tool versus alternatives. However, given the sibling tools are for different domains (e.g., DNS lookups, QR generation), the use case is implied. The pricing information provides some guidance on cost considerations, but no exclusion or alternative recommendations.

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 per-call pricing ($0.002 USDC via x402) and the inclusion of a rates table snapshot date. It does not explicitly state whether the tool is read-only, but the nature of a calculator implies no side effects. The pricing detail adds significant behavioral context.

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

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

The description is three concise sentences. The first sentence explains the core function and options, the second adds context about the rates table, and the third provides pricing. Every sentence adds unique value, and the most important information 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 the tool has 4 parameters and no output schema, the description covers the scope (EU-27+UK), directions, rates, and pricing. However, it does not hint at the response format (e.g., what the returned data looks like). This is a minor gap; otherwise, the context is adequate for a calculator 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 75%, and the description does not add new meaning beyond what the schema already provides. The schema already describes the parameters (rate with default, country as ISO code, direction with default). The description does not further clarify the 'amount' parameter or any edge cases, so it meets the baseline without extra value.

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 is a VAT calculator for EU-27 and UK, specifying the two calculation directions (net→gross, gross→net) and the two rate types (standard, reduced). It distinguishes itself from sibling tools (which are unrelated domains), making the purpose very specific.

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 EU/UK VAT calculations but does not explicitly state when to use or not use this tool. There are no sibling tools for comparison, so no alternative is mentioned. The pricing note is helpful but does not replace usage guidance.

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