Server Quality Checklist

Tool Scores

• custom_queryB
  3.1/5.0
  Behavior2/5

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

  With no annotations provided, the description carries the full burden of behavioral disclosure. While it mentions 'Apicalypse query' (implying a specific query language/syntax), it doesn't address authentication requirements, rate limits, error handling, response format, or whether this is a read-only vs. mutation operation. The description provides minimal behavioral context beyond the basic action.

  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 a single, efficient sentence that communicates the core functionality without any wasted words. It's appropriately sized for a tool with two parameters and good schema documentation, and the information is front-loaded with the essential action and target.

  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?

  Given the tool has an output schema (which handles return values), 100% parameter schema coverage, and no complex nested objects, the description is minimally adequate. However, for a flexible query tool with no annotations and specialized sibling tools, it should provide more guidance about when to use it versus the alternatives and more context about the Apicalypse query language.

  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?

  With 100% schema description coverage, the input schema already fully documents both parameters (endpoint and query). The description doesn't add meaningful semantic context beyond what's in the schema descriptions, such as explaining Apicalypse syntax in more detail or providing endpoint usage patterns. The baseline of 3 is appropriate when the schema does the heavy lifting.

  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 action ('Run a custom Apicalypse query') and target resource ('against any IGDB API endpoint'), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'search_games' or explain when to use this more flexible tool versus the specialized ones.

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

  Usage Guidelines2/5

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

  The description provides no guidance about when to use this tool versus the sibling tools (get_game_details, get_most_anticipated_games, search_games). There's no mention of prerequisites, alternatives, or specific scenarios where this custom query approach is preferable to the more specialized tools.

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

• search_gamesB
  3.1/5.0
  Behavior2/5

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

  No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool searches for games but doesn't describe key behaviors such as how results are sorted, whether it's paginated, if there are rate limits, or what authentication might be required. This leaves significant gaps for an agent to understand operational constraints.

  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 a single, efficient sentence: 'Search for games in the IGDB database'. It's front-loaded with the core action and resource, with no unnecessary words or redundancy. Every part of the sentence contributes directly to understanding the tool's purpose.

  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?

  Given the tool's moderate complexity (3 parameters, 1 required) and the presence of an output schema (which handles return values), the description is minimally adequate. However, it lacks context on behavioral traits (e.g., sorting, pagination) and usage guidelines relative to siblings, making it incomplete for optimal agent decision-making despite the structured support.

  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 description adds no parameter-specific information beyond what's already in the input schema, which has 100% coverage with clear descriptions for 'query', 'fields', and 'limit'. Since schema coverage is high, the baseline score is 3, as the description doesn't compensate with additional semantics like example queries or field usage tips.

  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's purpose: 'Search for games in the IGDB database'. It specifies the verb ('search') and resource ('games'), and identifies the database context. However, it doesn't explicitly differentiate from sibling tools like 'custom_query' or 'get_most_anticipated_games', which likely also involve game searches or queries.

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

  Usage Guidelines2/5

  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 doesn't mention sibling tools like 'custom_query' (which might offer more flexible queries) or 'get_game_details' (which might retrieve specific game information), nor does it specify contexts where this search is preferred over others. Usage is implied but not articulated.

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

• get_game_detailsB
  3.2/5.0
  Behavior2/5

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

  No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves information, implying a read-only operation, but does not cover aspects like rate limits, authentication needs, error handling, or response format. This is a significant gap for a tool with no annotation coverage.

  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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is appropriately sized and front-loaded, with every part earning its place.

  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 moderate complexity (2 parameters, 1 required), 100% schema coverage, and the presence of an output schema, the description is reasonably complete. It covers the core purpose, though it lacks behavioral details and usage guidelines, which are partially mitigated by the structured data.

  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 the schema already documents both parameters thoroughly. The description adds no additional meaning beyond what the schema provides, such as examples or constraints for the 'fields' parameter. Baseline 3 is appropriate when the schema does the heavy lifting.

  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 verb ('Retrieve') and resource ('detailed information about a specific game from IGDB'), making the purpose evident. However, it does not explicitly differentiate from sibling tools like 'search_games' or 'get_most_anticipated_games', which might also retrieve game information, so it lacks sibling distinction.

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

  Usage Guidelines2/5

  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 does not mention scenarios like needing details for a known game ID compared to searching by name or fetching anticipated games, leaving the agent without explicit usage context.

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

• get_most_anticipated_gamesB
  3.3/5.0
  Behavior2/5

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

  No annotations are provided, so the description carries full burden. It mentions sorting and filtering behavior, but lacks critical details: it doesn't specify if this is a read-only operation, whether it requires authentication, rate limits, pagination, or what happens with invalid parameters. For a tool with no annotations, this leaves significant behavioral gaps unaddressed.

  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 a single, efficient sentence that front-loads the core purpose without unnecessary words. Every element ('Fetch upcoming games', 'sorted by hype count', 'filtered for future or TBA releases') contributes directly to understanding the tool's function. It's appropriately sized for its complexity.

  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?

  Given 100% schema coverage and an output schema exists, the description doesn't need to explain parameters or return values. However, with no annotations and a tool that involves filtering and sorting, it should provide more behavioral context (e.g., read-only nature, error handling). It's minimally adequate but has clear gaps in transparency for a tool with this functionality.

  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 the schema fully documents all three parameters. The description adds no parameter-specific information beyond what's in the schema (e.g., it doesn't explain 'hypes' or 'TBA' in more detail). Baseline score of 3 is appropriate as the schema does the heavy lifting, but the description doesn't compensate with additional semantic context.

  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 action ('Fetch'), resource ('upcoming games'), and key sorting/filtering criteria ('sorted by hype count, filtered for future or TBA releases'). It distinguishes from siblings like 'get_game_details' (specific game) and 'search_games' (general search), though it doesn't explicitly name alternatives. The purpose is specific but could be slightly more distinct from 'custom_query'.

  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 implies usage for retrieving highly anticipated games based on hype, but provides no explicit guidance on when to use this tool versus alternatives like 'search_games' or 'custom_query'. It mentions filtering criteria but doesn't state prerequisites, exclusions, or comparative scenarios. Usage is contextually implied rather than explicitly defined.

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