mercury-x402-mcp

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

The description discloses key behaviors: output includes up/down, HTTP status, class, reachability reason, final URL, responseMs, and a signed receipt. It clarifies that the verdict is deterministic while responseMs is telemetry. With no annotations, this provides adequate 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, information-dense sentence followed by a succinct note on determinism and pricing. Every word adds value, with no redundancy or clutter.

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 simple input schema and no output schema, the description covers the essential output fields and behavioral nuances (signed receipt, determinism). Minor gaps exist (e.g., error handling, timeout behavior), but overall it is sufficiently complete for an agent to use the 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 has 100% coverage for the 'url' parameter, and the description adds significant context about how the URL is used (probing availability, returning signed evidence), beyond the schema's minimal description.

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

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

The description clearly states the tool's function: probing URL availability and providing signed evidence. It uses specific verbs like 'probe' and lists output fields (up/down, HTTP status, etc.), distinguishing it from siblings like 'fetch' or 'headers' that don't offer signed receipts.

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 usage guidance by mentioning the deterministic verdict, keyless operation, and pricing, implying when to use it (for provable SLA evidence). However, it lacks explicit comparisons to alternative tools like 'fetch' or 'redirect' for availability 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?

With no annotations, the description fully discloses key behaviors: deterministic (no LLM), SSRF-guarded, tamper-evident via Merkle proofs, cost $0.02/call, and authentication keyless x402 on Base mainnet. This exceeds typical transparency even with annotations.

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 efficient: a single sentence covering the core transformation, followed by concise bullet points on key features. Every sentence adds value (determinism, security, pricing) without 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?

The description covers input constraints, behavior, and cost, but lacks explicit response structure details (e.g., JSON format). Given no output schema, this omission is notable but partially mitigated by mentioning 'receipt' and 'proofs'.

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 tool description adds high-level context (e.g., 'Merkle leaf') but does not significantly enhance understanding of individual parameters beyond what the schema already provides (format enum, urls 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 the tool's function: taking a list of URLs (≤20) and returning clean content for each plus a signed receipt with a Merkle root. This specific verb+resource combination distinguishes it from sibling tools like fetch or extract, which handle single URLs.

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 usage context (batch processing of multiple URLs with verifiable integrity) but does not explicitly compare to alternatives. It is clear when to use (for 2-20 URLs requiring a receipt) but lacks guidance on when not to use, such as for single URLs or non-verifiable tasks.

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 statelessness, deterministic operation, signed receipts, pricing ($0.006/call), and keyless x402 on Base mainnet USDC. No contradictions or hidden 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 extremely concise: two sentences plus pricing. Every word adds value, front-loaded with the core purpose. No filler.

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 and no output schema, the description explains inputs, outputs (change-proof, receipt), and cost. It could mention output format details, but overall sufficiently complete for agent decision.

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 value by differentiating between using prevHash (hash-only change-proof) and prevText (full line-level diff). This clarifies behavior beyond the schema.

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

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

The description clearly states the tool's function: taking a URL and prior content hash or text, refetching, and producing a deterministic change-proof and a new signed receipt. It distinguishes itself from siblings like 'fetch' and 'notarize' by emphasizing diffing and tamper-evident audit trail.

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 cases (checking page changes, audit trail) but does not explicitly specify when to use this tool versus alternatives like 'fetch' or 'notarize'. No exclusions or prerequisites are mentioned.

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

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

No annotations exist, so the description carries the full burden. It discloses the tool is read-only (no mutation), produces signed/timestamped output, mentions determinism, and notes DNS mutability. However, it lacks details on error handling, rate limits, or response size, which would improve 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 moderately long but every sentence adds meaningful detail (purpose, normalization, verification, pricing). It could be slightly tighter (e.g., remove 'Keyless, no LLM, no signup' if not essential), but remains well-structured and 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 no output schema, the description provides a reasonable picture: a record set with a provenance receipt. However, it does not specify the structure or examples of the output, which an agent may need to parse the result correctly. The uniqueness among siblings compensates slightly.

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 description adds value by explaining that a URL's hostname is extracted and that domain is the primary parameter. This clarifies the alternative parameter and its behavior beyond the schema's basic 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 produces a signed, timestamped DNS snapshot with specific record types (A, AAAA, MX, NS, TXT, CNAME, SOA), normalized and sorted. This distinguishes it from sibling tools like fetch or headers which focus on HTTP responses.

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 DNS resolution and provenance but does not explicitly state when to use this tool versus alternatives like fetch or notarize. No exclusions or alternative tool names 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 fully carries the burden. It discloses deterministic extraction from page metadata, no LLM call, no API key, cost, payment method, signed provenance, SSRF guard, timeout, size cap, and that every call returns a structured result. 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?

The description is long but well-structured, front-loading the core purpose and then providing detailed behavior, cost, and payment details. It could trim some peripheral details (e.g., USDC on Base mainnet) but remains valuable.

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 thoroughly explains the return format (typed record with null for absent fields), input schema variants, extraction source, cost, timeout, SSRF guard, and comparison to siblings. It is fully complete for correct agent 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?

Schema coverage is 100% but the description adds significant value beyond the schema: it explains the compact schema format in detail, the alternative JSON-Schema object format, and clarifies the format parameter options. This greatly aids correct usage.

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 does typed structured extraction from a URL per a schema, returning a type-safe JSON record. It distinguishes itself from /buy/fetch by contrasting with their outputs, and the verb 'extract' directly matches the resource.

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 compares to /buy/fetch, stating when to use this tool (for schema-conformant objects) vs alternatives. It mentions the tool is deterministic, no LLM, no API key, but does not explicitly state 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 fully discloses behavioral details: deterministic output, normalization steps (CDATA unwrapped, HTML stripped, dates to ISO-8601), signed receipt via EIP-191, no fabricated dates, and cost per call. This is exceptionally transparent.

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

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

The description is a single dense sentence that efficiently packs purpose, normalization steps, output format, and cost. It is front-loaded with the key verb 'RSS/Atom feed URL → ... item list'. Minor clutter from em dashes 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?

The description fully covers input, processing, output fields, determinism, signing, and pricing. No output schema exists, but the return format is explicitly specified. For a tool with one parameter, this is highly 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?

There is only one parameter (url) with 100% schema description coverage. The description adds minimal additional meaning beyond the schema's 'the RSS/Atom feed to normalize (http/https)'. The baseline 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 takes an RSS/Atom feed URL and returns a signed, normalized item list. It specifies the unified format across RSS 2.0/RDF and Atom 1.0, and the concise title 'feed' combined with the sibling tools context (e.g., fetch, extract) makes its purpose distinct.

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 normalizing feed URLs into a standardized format with core fields. It doesn't explicitly state when not to use or mention alternative tools, but the sibling list and details like 'No LLM' and 'Core 4 fields only' provide contextual 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?

Discloses follow redirects, SSRF-guarded, 5s timeout, 10MB cap, charge-per-attempt with no silent failures, and the attestation mechanism. With no annotations, the description carries full burden and does so comprehensively.

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?

Front-loaded with key purpose but verbose with marketing language and comparisons. Every sentence adds value but could be more concise and structured for an AI agent. Still informative, but length reduces efficiency.

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?

Covers all aspects: what it returns, optional modes, attestation, charging, behaviors. Even without an output schema, description explains return structure (success or failure with reason). Complete for an agent to use the tool correctly.

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

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

Schema coverage is 100%, and description adds significant meaning: explains url (http/https), links (returns link graph), format (text vs markdown), extract (returns description+wordCount or JSON record for specified fields). Goes well beyond 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?

Clearly states 'VERIFIABLE keyless web-read for autonomous agents' and explains it fetches URLs returning clean text with optional structured extraction. Distinguishes from siblings by highlighting unique attestation capability and keyless access, contrasting with alternatives like Jina and Firecrawl.

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?

Describes use cases (RAG, trading, agent-to-agent commerce needing provenance) and contrasts with other services. Implicitly explains when to use (need verified data) but does not explicitly say when not to use or differentiate among 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 provided, so description bears full burden. It discloses deterministic nature, no LLM involvement, provenance receipt, and pricing ($0.005/call). Does not mention rate limits or side effects, but is transparent about core behavior.

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

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

Single sentence with high information density. Lists headers, output format, receipt, keyless nature, and pricing. No redundant words, front-loaded with main 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?

For a simple tool with one parameter and no output schema, the description covers purpose, input, output format, pricing, and uniqueness. No obvious 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 one parameter 'url' described. Description adds context that URL should be http/https for audit, but does not add significant new semantics beyond schema. 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 performs an HTTP security-headers audit, listing specific headers (HSTS, CSP, X-Frame, etc.) and outputs a letter grade and findings. It distinguishes itself from sibling tools like 'fetch' or 'metadata' by focusing on security audit.

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 or when-not to use guidance. Implied usage via 'deterministic' and 'Keyless, no LLM, no signup' but no comparison to siblings. Lacks 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?

No annotations are provided, so the description carries full burden. It discloses determinism (same input => same output), no LLM involvement, scope (only <a> hyperlinks), and pricing. It could mention failure modes or rate limits, but overall it provides key behavioral traits beyond the schema.

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

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

The description is a single, dense paragraph that front-loads the core purpose and then efficiently adds details like determinism, scope, signing, and pricing. Every sentence adds value with 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?

Given the lack of an output schema, the description adequately explains the output concept (signed link graph with classifications and counts) and mentions deterministic behavior and pricing. It could be more explicit about the output format (e.g., JSON), but the main functional context is covered.

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 one parameter (url) described as 'the page to map (http/https)'. The tool description adds minimal extra meaning beyond restating the input is a URL. The description's focus on output does not enhance parameter semantics, meeting the baseline for full 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 extracts all anchor links from a URL, classifies them as internal/external, groups by origin, and provides histograms and counts. It distinguishes itself from siblings by specifying it covers only <a> hyperlinks and produces a signed graph, which is unique among the sibling tools.

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

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

The description implies usage through the feature set but does not explicitly state when to use this tool over siblings like 'extract' or 'fetch'. It mentions limitations (only <a> tags) but lacks guidance on when not to use it or which alternative to choose.

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 the full burden. It discloses key behaviors: stripping of boilerplate/nav/ads, generation of a signed provenance receipt, determinism (byte-identical output for same input), and cost per call. It does not cover failure modes or edge cases, but provides sufficient transparency for an agent to understand the tool's behavior.

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

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

The description is a single, dense sentence that conveys all essential information without fluff. It is front-loaded with the core transformation and includes key differentiators (provenance, determinism, cost). Every phrase 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's simplicity (one parameter, no output schema) and the presence of many sibling tools, the description adequately explains the transformation, determinism, and cost. It could be improved by clarifying the structure of the receipt or differentiating more from 'readability', but overall it is sufficiently 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?

There is only one parameter ('url'), and its schema description already states 'the page to convert to markdown (http/https)'. The tool description does not add additional meaning beyond what the schema provides. With 100% schema description coverage, 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 that the tool converts a URL to clean, LLM-ready markdown by stripping boilerplate, navigation, and ads, while preserving headings, lists, and links. It also mentions a signed provenance receipt. This distinguishes it from sibling tools like 'readability' or 'extract' by positioning it as a RAG-ingest primitive.

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 that the tool is deterministic and has a fixed cost per call, which implies it is suitable for reliable, repeatable conversions without LLM involvement. However, it does not explicitly state when not to use this tool or recommend 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?

No annotations provided, so description carries full burden. It discloses determinism, keyless access, no LLM usage, and output signing. Cost per call is also mentioned. These traits are fully transparent and helpful for an agent's decision-making.

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 (two sentences) yet packed with information. It front-loads the core action and then lists specifics. 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?

No output schema, so description must cover return format. It lists all metadata types returned and mentions 'by source' organization. Missing error handling or edge cases, but sufficient 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?

Only one parameter (url) with 100% schema description coverage. The tool description adds context about return content but does not add new parameter-specific details beyond the schema. Baseline 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 explicitly states the tool returns a signed metadata record containing JSON-LD, OpenGraph, Twitter-card, standard meta, canonical, and title, organized by source. It clearly distinguishes from sibling tools by emphasizing determinism, keyless operation, and no LLM involvement.

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 obtaining verifiable structured metadata (social-card/SEO/schema.org). It does not explicitly state when not to use or compare to alternatives, but the context and sibling list provide some implicit guidance.

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

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

With no annotations, the description carries full burden. It discloses the hashing, timestamping, attestation, and deterministic nature. However, it does not explicitly state if the receipt is stored or how it is returned, and lacks rate limit info. Still, it provides good 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 a single, information-dense sentence with clear structure using dashes. It includes pricing and purpose, but could be slightly more concise by removing minor details. Still 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?

Without an output schema, the description should detail the return format. It mentions 'signed receipt' with hash and timestamp but not the structure (e.g., JSON, JWT). While it gives enough to infer, it's not fully explicit, leaving some ambiguity.

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

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

Schema coverage is 100% with detailed descriptions for both parameters, including mutual exclusivity and size limits. The description adds no extra parameter meaning beyond the schema, so baseline 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 verb 'notarize' and the resource 'content' into a 'signed, offline-verifiable provenance receipt'. It differentiates from sibling tools like fetch or extract by emphasizing it produces a cryptographic receipt with a third-party witness.

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 says when to use inline content or a fetched URL, and that they are mutually exclusive. It contrasts with sha256 alone and notes the cost, providing clear context for when to use this tool.

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

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

No annotations are provided, so the description carries the full burden. It thoroughly explains the deterministic nature (no LLM), stripping method (DOM density heuristics), output fields, provenance receipt, and cost per call. 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?

The description is front-loaded with the core transformation and is well-structured despite being long. Every sentence adds value (behavior, cost, differentiation). Could be slightly more concise, but still 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 fully covers the return format, deterministic behavior, stripping method, and cost. It provides enough context for an agent to use the tool correctly without ambiguity.

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

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

The single parameter (url) has 100% schema coverage with description. The tool description adds the constraint of http/https and max length, but does not add significant extra meaning beyond what the schema already provides. 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 converts a URL into a clean article record with specific fields (title, byline, etc.) and distinguishes itself from raw markdown via sibling tool reference. It uses a specific verb 'URL → a clean ARTICLE record' and explicitly calls out the differentiation.

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

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

The description implies usage for obtaining a clean-citation primitive versus raw markdown, and mentions deterministic behavior, but does not explicitly list when to avoid or compare to all siblings (e.g., fetch, extract). Still provides clear context for selection.

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

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

With no annotations, the description fully discloses key behaviors: only HTTP 3xx handling, no JS execution, deterministic, returns hop chain, cross-origin flag, and cost. Missing details on rate limits or timeouts, but adequate.

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 informative but dense, mixing many details (EIP-191 receipt, cost) that could be separated. It is not front-loaded in a concise manner.

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 simple input schema and the detailed description of outputs (hop chain, final URL, canonical, etc.), the tool is well-described for its purpose. It also states limitations.

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 fully covered by the schema description. The description adds no 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 it resolves a URL and provides redirect chain, final URL, canonical link, and safety signals. It distinguishes from siblings like fetch or headers by focusing on redirect resolution.

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 explains the tool's behavior (follows HTTP 3xx only, no JS/meta-refresh) and mentions deterministic results. However, it does not explicitly tell when to use this tool versus alternatives like fetch or metadata.

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 tool is deterministic, uses no LLM, provides signed output, lists data sources, and states cost. It does not cover failure modes or caching, but for a simple audit tool, the key behaviors are transparent.

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

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

The description is extremely concise—two sentences plus a cost note. It front-loads the core purpose and provides essential context without 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 the simple nature of the tool and high schema coverage, the description adequately covers what the tool does and its key characteristics. However, it lacks details about the return format (e.g., structure of the signed verdict), which would be helpful since there is 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 both parameters (path and domain) described. The description does not add significant semantic value beyond the schema; it repeats the domain concept but no new details like default behavior for path.

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 the tool audits robots.txt, llms.txt, and ai.txt for per-AI-crawler allow/block policies, producing a signed, timestamped verdict. It distinguishes itself from sibling tools like fetch or headers by focusing specifically on crawler policy evaluation.

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 verifying crawler permissions and mentions EU-AI-Act evidence, but it lacks explicit guidance on when not to use or alternatives. Given sibling tools, the context is manageable, but clearer when-not statements would improve.

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 fully discloses behavioral traits: deterministic signature for declared URLs, non-deterministic optional fetch not covered by signature, SSRF-guarded, bounded at every axis, and cost per call. This provides comprehensive transparency beyond what annotations would typically cover.

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

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

The description is a single dense sentence, but it is well-structured and front-loaded with the core purpose. It efficiently packs many details without redundancy. Minor points: it could be split into shorter sentences for readability, but overall it earns its space.

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

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

Given the tool's complexity (sitemap discovery, parsing, optional probe, signature, boundaries, cost), the description covers all essential behavioral aspects. No output schema is provided, but the description adequately describes the return value (URL inventory with attributes). It is complete enough for an AI agent to understand what the tool does and its constraints.

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 significant value beyond schema fields. For the 'url' parameter, it clarifies that only the origin is used. For 'fetch', it explains the range, behavior (shallow-fetch and report live title, status, bytes), and that results are not covered by the signature. For 'limit', it provides the default and maximum. This greatly aids correct invocation.

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 defines the tool's purpose: discovering and parsing a site's sitemap, returning a signed snapshot. It specifies the exact process (robots.txt then fallback, parsing both <urlset> and <sitemapindex>, deduped bounded list) and includes details like optional fetch. This distinguishes it from sibling tools like 'fetch' or 'robots' by focusing on sitemap-specific functionality.

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

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

The description explains when to use the tool (to get a signed sitemap snapshot) and briefly mentions optional features like fetch for liveness probing. However, it does not explicitly contrast with sibling tools or state when one should avoid using it. The context is clear but lacks explicit exclusions or comparisons.

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

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

No annotations exist, so the description carries behavioral burden. It discloses key traits: deterministic, no LLM, signed provenance receipt, and pricing. However, it omits failure modes, size limits, or behavior when no tables are found.

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

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

The description is relatively concise but includes technical jargon (x402, USDC on Base mainnet) that may not be essential for core tool usage. Information is front-loaded with the transformation 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?

Given three parameters and no output schema, the description explains the basic transformation but lacks details on error handling, limits, or response structure. It provides sufficient context for a straightforward tool but could be more 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%, so the description adds limited value beyond schema. It reiterates index and format options but does not provide deeper meaning or examples.

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 HTML tables from a URL and returns them as typed JSON and CSV. It distinguishes from sibling tools like 'extract', 'fetch', and 'markdown' by focusing specifically on table extraction.

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 mentions cost and determinism but does not explain scenarios where table extraction is appropriate or when siblings would be better.

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 of behavioral disclosure. It details determinism, keylessness, no LLM involvement, use of x402/USDC on Base mainnet, cost, and the exact output (pass/fail, per-field errors, signed provenance receipt binding verdict to response bytes and schema). 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?

The description is concise and well-structured: it starts with the core purpose, then elaborates on input format, behavior, and output. Every sentence adds necessary information without repetition.

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 moderate complexity (3 parameters, no output schema), the description thoroughly covers all aspects: input parameters with their variations, deterministic behavior, output details (pass/fail, errors, provenance), and cost. No 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 description coverage is 100%, and the description adds significant value beyond the schema. It explains the three accepted forms for the schema parameter (compact URL-native, JSON-Schema string, shorthand-map) and clarifies the optional pointer parameter for sub-document validation.

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 the tool validates a JSON/API endpoint against a JSON Schema, returning deterministic pass/fail with per-field errors and a signed provenance receipt. It clearly distinguishes from sibling tools which focus on different operations like fetching, diffing, or extracting 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 provides clear context for when to use this tool (deterministic, keyless validation without LLM) and mentions cost ($0.005/call). It does not explicitly state when not to use or compare with alternatives, but the differences from sibling tools are evident.

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