Server Quality Checklist

Tool Scores

• wikidata_queryB
  3.4/5.0
  Behavior3/5

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

  Given no annotations, the description is the only source for behavioral traits. It discloses limits (query length, timeout, max results) but does not state whether the tool is read-only, error handling, or response format. Partial disclosure.

  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 three sentences, front-loaded with purpose, immediately followed by limits and reuse suggestion. No unnecessary words; each sentence adds value.

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

  Completeness2/5

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

  No output schema is provided. The description fails to specify what the tool returns (e.g., JSON format, result structure), which is critical for a query tool. This missing detail reduces completeness.

  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 50% (only 'query' has description). The description adds context for timeout via '15s timeout' but does not explain the query parameter beyond 'SPARQL query string'. Marginal improvement over schema.

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

  Purpose4/5

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

  The description clearly states the tool is for Wikidata SPARQL queries and specifies use cases like people, places, organizations, factual relationships. It provides some differentiation from sibling tools (e.g., web, wiki, youtube) by focusing on structured data, but lacks explicit comparison.

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

  Usage Guidelines3/5

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

  The description includes constraints (5000 char limit, 15s timeout, 1000 max results) and suggests storing results in KG for reuse, but does not explicitly state when to use this tool versus alternatives or provide negative guidance.

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

• githubA
  4.3/5.0
  Behavior5/5

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

  With no annotations provided, the description fully carries the burden of behavioral disclosure. It reveals the return format ('{success, content/stats/results}'), response cap (2MB), caching (10min), and the harvest option for saving to disk. It also clearly states authentication requirements for write operations, providing critical behavioral transparency for an agent.

  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 concise opening sentence stating the overall purpose and return format, followed by a list of actions and important notes on auth, limits, and caching. It is efficient and front-loaded, though slightly lengthy due to the enumeration of actions, but every sentence adds value.

  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 (13 parameters, 8 actions) and absence of an output schema, the description covers the essential aspects: all actions, use cases, auth requirements, response limits, caching, and the harvest feature. Minor details like pagination for list_issues are omitted, but overall it provides sufficient context for correct tool invocation.

  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 every parameter is already described in the schema. The description does not add meaningful semantic detail beyond the schema; it merely lists actions and their purposes, which are already sufficiently documented. The baseline score of 3 is appropriate as the schema does the heavy lifting.

  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 provides 'GitHub file and repo access via API', lists specific actions (fetch, analyze, search, issue management), and distinguishes itself from sibling tools like fx, web, and wiki by focusing exclusively on GitHub operations.

  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 explicitly states use cases ('fetching source files, analyzing repo structure, searching code across GitHub') and lists all supported actions. It mentions that GITHUB_TOKEN is required for write operations and higher rate limits. However, it does not explicitly state when not to use the tool or provide direct comparisons to alternatives.

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

• wikiA
  4.3/5.0
  Behavior5/5

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

  With no annotations, description carries full burden. Discloses caching behavior ('Results cached 1hr.') and enumerates actions. No contradictions; clearly a read-only lookup.

  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?

  Two concise sentences with front-loaded purpose. Every sentence adds value: purpose, usage guideline, actions, caching. No unnecessary words.

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

  Completeness3/5

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

  Describes purpose, usage, actions, and caching. However, lacks explanation of parameter distinctions and return value (no output schema). Leaves gaps for an agent to understand fully.

  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 coverage is 0%, so description must compensate. It lists actions (search, page) which maps to action enum, but does not clarify when to use 'query' vs 'title' parameters. Partial help, but significant ambiguity remains.

  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?

  Clearly states 'Wikipedia lookup' which is a specific verb+resource. Distinguishes from siblings like wikidata_query and web search. Mentions two actions (search, page), adding clarity.

  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?

  Instructs to check memory/KG first, indicating proper usage order. Does not explicitly name alternatives or when not to use, but provides context for effective use.

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

• youtubeA
  4.6/5.0
  Behavior5/5

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

  No annotations provided, but the description fully discloses behavioral traits: fallback mechanism (primary vs yt-dlp), caching duration (1hr), auto-pagination with segment_offset, format defaults, and harvest behavior. 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.

  Conciseness3/5

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

  The description is a single dense paragraph covering many details. While all information is valuable, it could benefit from structuring (e.g., bullet points for actions) to improve scanability. It is not overly long but could be more concise.

  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 13 parameters and no output schema, the description thoroughly explains all aspects: actions, fallback, caching, pagination, harvest, format options, and search behavior. It is complete for an AI agent to select and invoke the tool correctly.

  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?

  With 100% schema description coverage, the baseline is 3, but the description adds substantial meaning: explains action semantics in detail, clarifies default formats and languages, describes harvest and pagination mechanics, and provides usage context for each parameter beyond 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?

  The description clearly states 'YouTube transcript and metadata tool' and enumerates specific actions (transcript, metadata, info, list_languages, search) with explicit roles for each, effectively distinguishing the tool's purpose from siblings.

  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?

  Provides usage guidance for each action, including best practices like using harvest=True for long podcasts and combining it with retrieve() for context efficiency. However, lacks explicit when-not-to-use guidance relative to sibling tools, though the tool's YouTube-specific scope naturally differentiates it.

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

• fxA
  4.7/5.0
  Behavior5/5

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

  Discloses persistence, default settings (images blocked, humanize off), waiting behavior (auto-waits for JS challenges), and side effects (harvest saves to disk). Without annotations, it fully carries the transparency burden and does so thoroughly.

  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 moderately lengthy but efficient, front-loading the purpose and then detailing actions and parameters. Every sentence adds value, though it could be slightly tighter in grouping related information.

  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 20 parameters and no output schema, the description covers major actions, defaults, and use cases well. It lacks explicit return value descriptions for some actions (e.g., screenshot, status), but overall provides sufficient completeness for effective use.

  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?

  All 20 parameters are described in the schema (100% coverage). The description adds meaningful context, such as explaining the roles of 'read' and 'navigate', and clarifying defaults for wait_until and stealth. This enhances understanding beyond the raw 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?

  Clearly identifies as 'Anti-detect Firefox browser' with a specific use case (when web crawl fails due to bot protection). Distinguishes itself from sibling tools like 'web' by offering browser-level automation with anti-detection features.

  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 on when to use: 'Use when web(crawl) fails due to bot protection'. Differentiates between 'read' for one-shot extraction and 'navigate' for multi-step workflows, and advises when to call 'close'.

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

• webA
  5/5.0
  Behavior5/5

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

  With no annotations, the description fully discloses: caching (20 min), high context cost, harvest behavior, default summary, news endpoint fields, timeout default. 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.

  Conciseness5/5

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

  Compact paragraph with front-loaded purpose and clear logical flow: purpose, usage order, action details, news, cost mitigation, caching, alternatives. Every sentence adds value.

  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 9 parameters and no output schema, the description covers all essential aspects: what it does, how to use, parameter details, behavior, caching, context management, and alternative tool.

  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 coverage is 100%, but description adds meaning: groups actions, explains harvest as context-saving, news adds date/source, timelimit for news, harvest_dest subfolder, summary default true.

  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?

  Clearly states 'Web search and page fetching' and specifies two actions (search via DuckDuckGo, crawl via URL fetch). Explicitly distinguishes from sibling tool fx for bot-protected sites.

  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 usage order: 'Use ONLY after exhausting local sources: retrieve() -> kg(neighbors) -> web.' Also advises using fx for bot-protected sites and suggests harvest=True to save context.

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