Server Quality Checklist

Tool Scores

• web_fetch_sectionsA
  4/5.0
  Behavior4/5

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

  The description adds substantial behavioral context beyond the readOnlyHint, such as being a 'cheap structural preview' that 'avoids pulling the page body', resolving URL fragments, and returning a comment tree with metadata for Reddit. This enriches the agent's understanding of what the tool does and what it returns, though it does not cover every edge case.

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

  Conciseness4/5

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

  The description is well-structured with a clear opening sentence, detailed usage guidance, and a separate Reddit note. It is slightly longer than necessary but every sentence contributes value, and the main purpose is front-loaded.

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

  Completeness4/5

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

  The description is largely complete for a tool with two parameters and no output schema. It covers purpose, typical usage, URL fragment handling, and Reddit-specific behavior. However, the unexplained 'slice' parameter leaves a notable gap in contextual completeness.

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

  Parameters1/5

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

  The schema has 0% description coverage, and the description does not explain the 'slice' parameter at all. The only mention of 'slices' refers to the follow-up tool web_fetch_incisive, not this tool's slice parameter. The description fails to compensate for the missing schema descriptions, leaving the agent without guidance on how to use 'slice'.

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

  Purpose5/5

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

  The description opens with 'List a document's section headings to understand page composition or plan targeted extraction,' providing a specific verb, resource, and intended use. It clearly distinguishes itself from web_fetch_incisive by positioning it as a preliminary structural preview.

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

  Usage Guidelines5/5

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

  The description explicitly states the workflow: 'call this first... then follow up with web_fetch_incisive using the returned heading names as section= or slugs as slices='. It also provides Reddit-specific guidance, making the when-to-use unambiguous.

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

• ietfA
  4.1/5.0
  Behavior4/5

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

  Annotations only include readOnlyHint=true, so the description carries the burden of behavioral disclosure. It adds valuable context: the tool supports multiple actions, RFCs have native DOIs, and inspected RFCs are 'automatically tracked on the research shelf.' No contradictions 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.

  Conciseness4/5

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

  The description is well-structured with headers like 'Actions:' and 'Query formats:', and it front-loads the core purpose. While it is fairly long, each section serves a function and avoids fluff. Slight redundancy with schema descriptions but acceptable for a multi-action tool.

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

  Completeness4/5

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

  For a complex tool with 6 parameters and 4 actions but no output schema, the description explains the purpose of each action and provides query format examples. It also notes integration with web_fetch_incisive and the research shelf. It doesn't describe return structures, but the lack of an output schema makes this a minor gap.

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

  Parameters3/5

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

  Schema description coverage is 100%, with detailed descriptions for every parameter (action, query, status, wg, limit, offset). The tool description's 'Query formats' section essentially paraphrases the schema, adding little new parameter-level meaning beyond what the schema already provides.

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

  Purpose5/5

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

  The description opens with a specific verb and resource: 'Search and retrieve IETF RFCs, Internet-Drafts, and standards-track documents.' It then enumerates distinct actions (rfc, search, draft, subseries), clearly distinguishing this tool from siblings like arxiv or web_fetch_sections.

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

  Usage Guidelines4/5

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

  The description states 'Use this for RFC lookups' and lists concrete use cases. It also notes that 'RFC Editor and Datatracker URLs are also handled automatically by web_fetch_incisive,' which provides an alternative tool for URL input. However, it doesn't fully elaborate when to prefer other siblings like arxiv or kagi_search.

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

• kagi_searchA
  4.5/5.0
  Behavior5/5

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

  Beyond the readOnlyHint annotation, the description or its schema-rich parameter docs disclose stable pagination (same page returns identical results), deduplication needs across pages, silent failures for invalid lens slugs, and strict ISO date format pitfall. These behavioral traits are not in annotations and add significant safety context.

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

  Conciseness4/5

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

  The description is front-loaded with purpose and alternative usage in the first sentence. It is relatively long (two paragraphs) but every sentence contributes either purpose, usage context, or a parameter summary; given the 8-parameter complexity, the length is justified.

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

  Completeness4/5

  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's mention of 'compact results with snippets and timestamps' partially covers return value expectations. It provides strong coverage of purpose, usage, and edge cases; the only minor gap is a full description of the response shape, but this is acceptable for a search tool.

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

  Parameters3/5

  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's parameter summary (workflow=, limit=, lens_id=, page=, region=, after=, before=) is a helpful overview but adds no new details beyond what the schema already provides. The operator syntax list is also fully duplicated in the query parameter description.

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

  Purpose5/5

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

  The description opens with a specific verb+resource: 'Search the web using Kagi's curated search index.' It immediately distinguishes from siblings by naming web_search as an alternative and stating Kagi's differentiators (curated, SEO-spam resistant, different sources).

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

  Usage Guidelines5/5

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

  Explicitly states when to use this tool: 'Use this as an alternative to web_search when it returns few or poor quality results.' Also provides context on when it is better suited (multi-query research workflows) and what it returns (compact results, lighter on context).

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

• research_shelfA
  4.5/5.0
  Behavior5/5

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

  Beyond the destructiveHint annotation, the description discloses in-memory storage, survival across context compaction, auto-add behavior, import merge semantics, and the cross-session export/import workflow. It also clarifies destructive actions like clear and remove.

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

  Conciseness4/5

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

  The description opens with a clear one-sentence purpose and uses structured sections for actions and query formats. It is long, but the length is justified by eight distinct actions and their syntax; no content is filler, though some redundancy with the schema exists.

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

  Completeness4/5

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

  Given the tool's complexity (8 actions, query formats, auto-population sources, persistence), the description covers all essential usage aspects. It does not describe return values or error behavior, but the detailed schema and annotations make it sufficient for correct selection and invocation.

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

  Parameters4/5

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

  The schema already covers both parameters at 100%, but the description adds a readable, example-driven query format list and the important detail that import merges with the current shelf, which is not in the schema's import description. This enhances usability beyond the structured fields.

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

  Purpose5/5

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

  The description clearly states this tool manages an in-memory research shelf for tracking papers, with specific verbs: review, score, confirm, remove, export. It distinguishes itself from source-fetching sibling tools by focusing on post-discovery management and listing the tools that auto-populate the shelf.

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

  Usage Guidelines4/5

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

  The description explains when to use this tool: after research tools like arxiv, semantic_scholar, ietf, github, or web_fetch_incisive have resolved papers. It gives clear context for managing tracked entries and cross-session persistence, though it does not explicitly state when not to use it or name direct alternatives.

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

• githubA
  4.6/5.0
  Behavior4/5

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

  Annotations already declare readOnlyHint=true, so the description adds value beyond that by disclosing authentication requirements (GITHUB_TOKEN), rate limits (5000 vs 60 req/hr), and the context-specific behavior of issue_templates. It does not contradict annotations, though it does not describe the return format in detail.

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

  Conciseness5/5

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

  Though lengthy, the description is well-structured with bullets and action lists. Every sentence earns its place: summary, usage context, action list, query formats, and authentication details. Front-loaded with the purpose, it avoids unnecessary verbosity.

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

  Completeness4/5

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

  Given the complexity (9 actions, 5 parameters, no output schema), the description covers all actions, query formats, authentication, and selective usage guidance. Return values are not explicitly stated, but the schema's action property descriptions already include details like 'get issue details + comments', so the description is adequately complete.

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

  Parameters4/5

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

  Schema coverage is 100%, so baseline 3. The description adds value by providing concrete query format examples for each action (e.g., owner/repo#number, owner/repo/path) and clarifying the ref= parameter usage, exceeding what the schema alone offers.

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

  Purpose5/5

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

  The description clearly states it searches and retrieves code, issues, pull requests, and repositories from GitHub, listing all nine actions explicitly. It also distinguishes itself from web_fetch_incisive by stating that tool handles GitHub URLs, 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.

  Usage Guidelines5/5

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

  Provides explicit guidance: 'Use this for GitHub lookups...' and contrasts with web_fetch_incisive for URLs. It also advises when to call issue_templates (before filing if the repo action's frontmatter hints at custom submission flow), giving clear when-to-use context.

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

• arxivA
  4.7/5.0
  Behavior5/5

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

  Annotations already declare readOnlyHint=true, so the safety profile is known. The description adds valuable behavioral context including the three action modes, the non-natural-language query syntax, and the side effect that 'Papers retrieved via the paper action are automatically tracked on the research shelf.' No contradictions with annotations exist.

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

  Conciseness5/5

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

  The description is well structured with sections for Actions, Query Formats, and Search Operators, plus examples. Every sentence contributes functional guidance, making it appropriately sized for a tool with three distinct actions and a complex query language. It is concise relative to its complexity.

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

  Completeness5/5

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

  With no output schema, the description must explain return values and does so by listing what paper details are retrievable (abstract, authors, categories, affiliations, DOI, journal refs). It also covers category browsing, query formats, and side effects, making the tool's behavior fully comprehensible to an agent.

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

  Parameters3/5

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

  The input schema provides 100% coverage with highly detailed descriptions for every parameter, including query syntax, examples, and defaults. The description partially duplicates this information but adds the research-shelf tracking side effect and a condensed operator reference. Since the schema carries the heavy lifting, 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.

  Purpose5/5

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

  The description clearly states 'Search and retrieve academic papers from arXiv,' providing a specific verb and resource. It further enumerates the three distinct actions (search, paper, category) and explicitly notes that arXiv URLs are also handled by web_fetch_incisive, which differentiates this tool from its siblings.

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

  Usage Guidelines5/5

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

  The description explicitly opens with 'Use this for arXiv paper lookups' and then lists concrete scenarios. It also provides an exclusion by stating 'arXiv abstract and PDF URLs are also handled automatically by web_fetch_incisive,' telling the agent when to use a different tool. This is clear guidance on when to use versus alternatives.

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

• discourseA
  4.7/5.0
  Behavior4/5

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

  Annotations already declare readOnlyHint=true. The description adds useful behavioral context: no auth required for public forums, base_url inference for topic, and how the query parameter is interpreted per action. It does not mention rate limits or response format, but for a read-only tool the added context is solid.

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

  Conciseness5/5

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

  The description is well-structured: opening purpose sentence, usage context, action list, query formats, and closure on auth. Every sentence earns its place; no fluff. Front-loaded with the key verb and resource.

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

  Completeness5/5

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

  For a 4-parameter tool with no output schema, the description covers action selection, parameter roles, required vs optional fields, base_url inference, and authentication. It gives enough context for an agent to correctly pick and invoke the tool without ambiguity.

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

  Parameters4/5

  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 value beyond the schema by giving concrete query format examples, explaining base_url inference, and clarifying that 'latest' ignores the query parameter. This helps an agent understand parameter interplay.

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

  Purpose5/5

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

  The description clearly states 'Search and browse Discourse forum topics' with a specific verb and resource. It explicitly distinguishes itself from web_fetch_incisive by noting that tool auto-detects Discourse URLs, positioning this tool as the structured-query alternative.

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

  Usage Guidelines5/5

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

  Provides explicit when-to-use guidance: 'Use this for Discourse forum lookups' and contrasts with the sibling tool ('Discourse URLs are also detected automatically by web_fetch_incisive... this tool is for structured queries when you know the forum's base URL'). Also details action-specific requirements (base_url required for search/latest, inferred for topic).

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

• packagesA
  4.7/5.0
  Behavior4/5

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

  The readOnlyHint annotation is supported by the 'Search and inspect' wording, and the description adds useful behavioral context such as supported ecosystems and queried data types. It does not mention rate limits or return format, but the annotation covers the safety profile and the added context is substantial.

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

  Conciseness5/5

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

  The description is well-structured with a front-loaded purpose, bulleted actions, query formats, and a final alternative note. Every sentence contributes information without unnecessary repetition or padding.

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

  Completeness5/5

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

  For a read-only tool with two parameters and no output schema, it covers all actions, query formats, ecosystem aliases, and exclusions. An agent can correctly select the action and construct a valid query without needing external documentation.

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

  Parameters4/5

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

  Input schema already documents both parameters at 100% coverage, but the description adds value with ecosystem aliases, concrete examples like 'pypi/requests@2.32.3', and the rule that query format depends on action. This goes beyond the schema's generic property descriptions.

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

  Purpose5/5

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

  The description opens with a specific verb-resource pairing: 'Search and inspect software packages across language ecosystems via deps.dev' and lists concrete data types (version history, licenses, security advisories, etc.). It also distinguishes itself from sibling tools by explicitly naming alternatives for repository details.

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

  Usage Guidelines5/5

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

  It includes 'Use this for package lookups' followed by specific use cases, then a clear exclusion: 'For repository details ... use web_fetch_incisive or github.' The action/query format section provides per-action guidance on when to use each operation.

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

• huggingfaceA
  4.8/5.0
  Behavior5/5

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

  The readOnlyHint annotation is minimal, but the description provides extensive behavioral disclosure: weight files are never downloaded, effective bits-per-weight suppression cases, the extra request for quant_audit, and the 401 ambiguity without a token. This goes well beyond what annotations convey.

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

  Conciseness4/5

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

  The description is long but well-organized and information-dense. It front-loads the core purpose, then systematically covers actions, caveats, and auth. Every sentence adds value, though a few could be tightened. For the tool's complexity, the length is justified.

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

  Completeness5/5

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

  For a multi-action tool with 7 parameters and no output schema, the description covers all major aspects: return behavior, edge cases, authentication, and per-action semantics. It also explains when quant_audit is valuable and what happens without a token. Highly complete.

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

  Parameters4/5

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

  Schema descriptions cover all 7 parameters, but the description adds meaningful context: query format examples for each action, the substring behavior of Hub search, what ref= means, and the byte-range recipe detail. It adds nuance beyond a simple restatement of the schema.

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

  Purpose5/5

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

  Opening sentence clearly states the verb (Inspect) and resource (HuggingFace Hub models), then enumerates what is inspected: metadata, files, quantization quality. The description also distinguishes itself from web_fetch_incisive by explicitly noting it is for structured queries, not URL fetching.

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

  Usage Guidelines5/5

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

  Explicitly states 'Use this for model-repo lookups' and enumerates the exact types of lookups. It names the alternative (web_fetch_incisive) for URL handling, and provides action-specific query formats. This gives the agent clear when-to-use and 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.

• mediawikiA
  4.8/5.0
  Behavior5/5

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

  The description richly discloses behavioral traits beyond the readOnlyHint annotation: case-insensitivity, no stemming, silent dropping of punctuation, character n-gram indexing for CJK scripts, URL-priority over wiki=, dispatcher rejection of mismatched parameters, and the behavior of search operators. This provides deep insight into how the tool executes, which annotations alone do not convey.

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

  Conciseness4/5

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

  The description is long but well-structured with clear sections (Actions, PARAMETER SPLIT, Query formats, search= operators, Wiki instance). It is front-loaded with the primary purpose. However, the extensive operator details and lengthy examples could be trimmed; some sentences are redundant with the schema (e.g., action descriptions). Overall, it earns a slightly above-average score for organization but loses points for verbosity.

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

  Completeness4/5

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

  The description is extremely thorough on input semantics, covering all parameters, edge cases, and operator syntax. However, with no output schema, it does not describe the structure of the returned content (e.g., what fields are present in a page fetch or search result). This is a notable gap for a tool with multiple actions and no return type documentation, keeping it from a perfect score.

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

  Parameters5/5

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

  Even though schema coverage is 100%, the description adds substantial meaning: it explains the title/query split, the distinct meanings of 'search' (within-page) vs query (full-text), the footnotes/citations formats, and detailed query syntax. For example, it clarifies that 'search=' uses tantivy query language while 'query=' supports MediaWiki operators, which is not apparent from the schema alone.

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

  Purpose5/5

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

  The description opens with a specific verb and resource: 'Search and retrieve content from Wikipedia and other MediaWiki sites.' It clearly distinguishes from siblings by noting it avoids web_search with site: filters and that web_fetch_incisive handles URLs automatically. The action list (page, search, references) further clarifies the scope.

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

  Usage Guidelines5/5

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

  Explicit guidance is provided: 'Use this for direct Wikipedia access without resorting to web_search with site: filters.' It also mentions when web_fetch_incisive is the appropriate alternative for URL handling. The parameter-split explanation ('PARAMETER SPLIT') tells the agent exactly which parameters to use for each action, preventing misuse.

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

• web_fetch_incisiveA
  5/5.0
  Behavior5/5

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

  Annotations only include readOnlyHint: true, but the description goes far beyond this. It discloses that the fetch happens through the user's device, reddit HTML/JS behavior, 'a plain fallback returns static HTML', 'requires_js is the heavier path', and that response frontmatter contains signals. There is no contradiction with readOnlyHint; the operation is a read.

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

  Conciseness5/5

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

  The description is long but exceptionally well structured. It uses bold labels (TARGETED EXTRACTION, READ WORKFLOW, READTION CHAIN and OPERATORS) and lists, breaking the content (browsing into scannable pieces). Every section earns its cost; no wasted sentences or vague filler.

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

  Completeness5/5

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

  With 9 params, zero schema coverage, and no output schema, this description is as thorough as one could expect. It explains the core purpose, extraction modes, search semantics, JavaScript fallbacks, Reddit scope, and the frontmatter signal. It gives an agent everything needed to choose correctly and call the tool productively.

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

  Parameters5/5

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

  Schema description coverage is 0%, but the description fully compensates. It explains each extraction parameter: section, autoexpand, search with full operator syntax, slices, URL fragments, brackets for actions, requires_js, and the max_elements cap on the annotated interactive-element list. It also covers edge cases like East Asian n-gram matching and Reddit thread caching.

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

  Purpose5/5

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

  The description is explicit and precise: 'Fetch and extract unsummarized content from URLs as markdown.' It describes a specific verb, resource, and output format, and differentiates itself from the web_fetch sibling by noting it fetches through the user's device and uses precise extraction instead of summarization.

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

  Usage Guidelines5/5

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

  The description gives extensive when-to-use guidance: 'Use this for a rich content exploring experience... not subject to 403 bans... or when web_fetch is rejected with PERMISSIONS_ERROR.' It explicitly recommends a workflow: 'call web_fetch_sections first... then come back here.' It also provides a hard rule: 'Always use this tool for Reddit URLs' and tells when to use alternative or additional tools like the MediaWiki companion.

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

• youtubeA
  5/5.0
  Behavior5/5

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

  Beyond the readOnlyHint annotation, the description discloses authentication requirements, bot-detection/PoTokenRequired failure modes, residential-proxy fallback, flat-extraction stub behavior, and adaptive chunking behavior. It adds rich operational context without contradicting the read-only annotation.

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

  Conciseness5/5

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

  The description is long but tightly structured with labeled sections and bullet-like lists. It is front-loaded with the core purpose and action split, and every sentence conveys actionable operational detail rather than filler.

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

  Completeness5/5

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

  For a 12-parameter tool with no output schema, the description is remarkably complete: it covers return shapes (stub entries, frontmatter fields, transcript formats), error conditions, workarounds, and hints for callers (e.g., the see_also pivot to youtube_comments). An agent has enough context to select and invoke the tool correctly in most scenarios.

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

  Parameters5/5

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

  Even though the schema covers all 12 parameters, the description substantially adds meaning: the action/url/query split, URL format variants per action, mutual exclusivity (e.g., windows vs search), defaults, timestamp modes, and how limit interacts with yt-dlp's playlistend. This goes far beyond the schema's field descriptions.

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

  Purpose5/5

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

  The description opens with a specific verb-plus-resource statement ('Fetch YouTube content via yt-dlp and youtube-transcript-api') and enumerates five concrete actions (video, transcript, channel, playlist, search) with distinct outputs. It clearly differentiates from sibling tools like youtube_comments and web_fetch_incisive.

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

  Usage Guidelines5/5

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

  It explicitly states when to use this tool ('Use this for YouTube lookups when web_fetch_incisive doesn't apply') and lists the exact use cases it covers. It also identifies exclusions and alternatives: comments are handled by the dedicated youtube_comments tool and music.youtube.com URLs are out of scope for a sibling tool.

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

• youtube_commentsA
  5/5.0
  Behavior5/5

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

  Beyond the readOnlyHint annotation, the description discloses key behaviors: top-level comments are sorted by 'top' with no replies, thread view shows up to 50 replies, no authentication required, and errors like bot detection are surfaced as user-facing strings. This adds substantial 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.

  Conciseness5/5

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

  The description is well-structured with a front-loaded summary, clear sections for the two views, usage flow, URL formats, and error handling. Every sentence adds value, and the format aids quick comprehension despite its length.

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

  Completeness5/5

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

  Given the tool's complexity (two views, no output schema, interactions with YouTube), the description is complete: it covers how to use it, what to expect in returns, limitations (cap, no replies in overview), and failure modes. It leaves little ambiguity for an agent.

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

  Parameters5/5

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

  Even though schema coverage is 100%, the description adds meaning beyond the schema: comment_id selects the thread view, limit caps the overview and is ignored with comment_id set, and the comment id source is described as coming from the overview's id field. This enriches the parameter semantics.

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

  Purpose5/5

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

  The description opens with a specific verb and resource: 'Read YouTube video comments: top-level overview or per-thread drill-down.' It explicitly distinguishes itself from the sibling 'youtube' tool by stating 'The video tool returns the description; this tool returns the conversation,' making its purpose unambiguous.

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

  Usage Guidelines5/5

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

  It provides explicit when-to-use guidance: 'Pivot from youtube when the goal is to read what viewers are saying about a video.' It also explains the two usage modes (overview vs. thread) based on comment_id, giving clear context for selecting this tool over alternatives.

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