Server Quality Checklist

Tool Scores

• resolve_musicA
  4.2/5.0
  Behavior3/5

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

  No annotations provided, so description carries full burden. It discloses ranking logic (trust × price × availability, no commission) but does not describe output format, error cases, or side effects. Adequate but not comprehensive.

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

  Conciseness5/5

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

  Four sentences, each adding value: action, result, usage context, and ranking philosophy. No wasted words, front-loaded with the main purpose.

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

  Completeness4/5

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

  For a single-parameter tool with no output schema, the description provides sufficient context about what the tool does and how results are ranked. Could mention that results are ranked and what sources are included, which it does. Lacks detail on output structure (e.g., links, prices) but is adequate for an AI agent.

  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% with a clear description of 'slug' format and example ('ed-sheeran-galway-girl'). Description adds value by explaining the parameter's purpose and expected format 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 uses a specific verb ('resolve') and resource ('song or album'), clearly stating it finds streaming, purchase, and physical media options. It distinguishes from siblings like 'discover_music' (discovery) and 'resolve_game' (games).

  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?

  Explicitly says 'Use when a user asks about music' and lists scenarios (listen, own digitally, collector). Does not explicitly mention when not to use or contrast with siblings, but the context is clear.

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

• discover_musicA
  4.3/5.0
  Behavior4/5

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

  No annotations provided, so the description carries full burden. It discloses ranking criteria ('Ranked by editorial pinning and refresh freshness, never by commission'), the structure of responses (foyer/chamber/wall), and mentions further resolution via resolve_music. This adds valuable behavioral context 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.

  Conciseness4/5

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

  The description is well-structured, starting with the main purpose and then providing examples and details. It is a bit lengthy (6 sentences) but every sentence adds value, so conciseness is good but not perfect.

  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?

  No output schema, but the description explains what is returned: walls with slugs and entries with BeatsVine page URLs. It covers the main use cases and the flow of drilling down. For a browsing tool with 3 optional params, this is fairly complete. Could mention pagination or error cases, but not necessary.

  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 is 3. The description enriches the parameter meanings by explaining the chambers ('by-genre' = genre corridors, etc.), how wall slugs are obtained and used, and the limit applies to different modes. This adds practical context 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 uses specific verbs and resources ('Browse curated music collections') and includes concrete examples like 'what's trending this week' and 'show me focus playlists'. It clearly differentiates from sibling tools like resolve_music, which handles URL resolution, and find_product/resolve_game.

  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?

  Explicitly states when to use ('when a user wants to EXPLORE music rather than look up a specific song or album'). It explains the flow of using returned slugs with the `wall` argument. However, it does not explicitly state when not to use it, though the context is clear.

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

• resolve_gameA
  4.4/5.0
  Behavior4/5

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

  With no annotations provided, the description carries the full burden of disclosure. It transparently notes the tool is currently non-functional, returning a 'coming soon' message, which is a key behavioral trait. However, it does not explicitly mention read-only nature or other 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.

  Conciseness5/5

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

  The description is concise and well-structured: a single sentence for purpose, a second for details, and a crucial note about current status. Every sentence adds value without repetition.

  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 no output schema, the description explains the return format (ranked results with prices, editions, DLC info) and the current limitation. It covers the stores list. It is mostly complete but lacks mention of error handling or data freshness.

  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 schema coverage is 100% for the single required parameter. The description adds no additional meaning beyond the schema, repeating the slug format and example from the schema. Thus, the 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 the tool's purpose: finding where to buy a video game at the best price across specific trusted stores. It distinguishes itself from siblings by targeting games versus music.

  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 not only explains when to use the tool (for game purchases) but also advises when not to use it (for music queries) and provides alternatives (`resolve_music` or `find_product`), fulfilling the guidelines dimension well.

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

• find_productA
  4.6/5.0
  Behavior4/5

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

  No annotations are provided, so the description must fully disclose behavior. It explains auto-detection of product category, routing to resolvers, and states which categories are live and which are rolling out. It lacks explicit details on authentication or rate limits, but for a non-destructive routing tool, this is reasonably transparent.

  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 concise and well-structured, starting with the core purpose ('Smart router'), then detailing supported categories and usage guidance. Every sentence adds value without redundancy.

  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 (routing, multiple categories) and lack of output schema, the description adequately explains behavior, status, and when to use. It could mention fallback behavior for unsupported categories, but overall it is complete enough for an agent to use correctly.

  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 input schema has 100% coverage with descriptions for both parameters. The description adds context by explaining the 'query' parameter with natural language examples and the 'category' enum with the 'auto' default. This exceeds the baseline of 3 by providing meaningful usage context.

  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 explicitly states it is a 'Smart router' that finds the best place to stream, buy, or collect products. It specifies the product categories (music, games, etc.) and clearly distinguishes from sibling tools like discover_music, resolve_game, and resolve_music.

  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 provides explicit guidance: 'Use this when the query is ambiguous or when music could be streamed, purchased digitally, or found on physical media.' It also explains the category parameter's auto-detect behavior, helping the agent decide when to use 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.