Server Quality Checklist

Tool Scores

• get_recipeA
  4.5/5.0
  Behavior4/5

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

  While annotations already indicate read-only, idempotent, and non-destructive, the description adds important behavioral details such as how scaling flags work ('scaled', 'rounded', 'unscaled'), the rationale to avoid non-integer quantities, and the yield field for pieces. This goes beyond the annotations, though it doesn't cover all edge cases like error handling or rate limits, but the additions are substantial.

  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 fairly long but each sentence provides necessary detail, especially the scaling explanation, which is critical for correct usage. It front-loads the core purpose and then dives into specifics. The length is justified, though it could be slightly more streamlined, but it's effective and not wasteful.

  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, the description covers the key aspects: input parameters, scaling behavior, yield, and citation requirement. The output schema likely details return structure, so the description doesn't need to repeat that. Annotations cover safety, and the description fills in usage nuances. A few edge cases (e.g., what happens if id not found) aren't mentioned, but overall it's comprehensive for the use case.

  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 the baseline is 3, but the description adds extra semantics for the 'servings' parameter, explaining the scaling behavior and the flag system. For 'id' and 'url', it clarifies the preference and precedence rules beyond what the schema states (e.g., 'Preferred over url', 'Ignored when id is given'). This adds meaningful value, justifying a 4.

  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 reads a single Marmiton recipe with specific content (ingredients, steps, times, category, rating, nutrition). It distinguishes itself from sibling tools by referencing search_recipes for obtaining the id and by handling scaling differently from the separate scale_ingredients tool.

  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 on when to use this tool: provides the id from search_recipes or a marmiton.org URL, with clear alternatives and exclusions (URL ignored if id given, only marmiton.org accepted). It also instructs when to omit servings and when to use scaling flags, and mentions citing attribution, which effectively covers usage context.

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

• scale_ingredientsA
  4.5/5.0
  Behavior5/5

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

  The description discloses detailed behavior: quantities are multiplied and rounded, countable items are handled with fractions, approximate measures stay whole, and lines without quantities are flagged. This goes beyond annotations (readOnly, idempotent) and fully informs the user of the tool's effects.

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

  Conciseness2/5

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

  The description is overly verbose and repetitive. For example, the sentence about countable items and approximate measures is long, and the final sentence about 'A line writing an article where a digit would go' restates earlier content. This could be condensed without losing meaning.

  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?

  The description covers all necessary aspects: what the tool does, how to specify scaling, handling of different unit types, and behavior for missing quantities. It is complete enough for an agent to use the tool effectively without additional clarification.

  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?

  The description adds meaning to parameters: it explains the relationship between factor and from_servings/to_servings, and clarifies that ingredients are lines that may contain quantities. It also describes how lines without quantities are treated, providing more context than the schema 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 clearly states the tool's purpose: 'Rescale a list of ingredient lines to a different number of servings'. It also specifies the input type (French ingredient list) and distinguishes it from sibling tools (search_recipes, get_recipe) by focusing on scaling.

  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 provides explicit usage instructions: 'Give either factor directly, or from_servings and to_servings'. It also gives examples and notes about rounding and edge cases, but does not explicitly state when to prefer this tool over siblings, though the purpose is clear enough.

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

• search_recipesA
  4.5/5.0
  Behavior4/5

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

  Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false, and the description does not contradict them. It adds valuable context about the one-page result and robots.txt restriction, plus the return of ids and URLs, enriching the behavioral picture beyond the annotations.

  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, with each sentence serving a distinct purpose: purpose, examples, result guidance, and pagination constraint. There is no redundancy or fluff.

  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 simplicity and the presence of an output schema, the description covers all necessary aspects: search intent, language considerations, result format, and pagination constraints. It is complete for an agent to understand and use the tool effectively.

  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 fully describes both parameters, but the description enriches the query parameter with examples and language guidance (e.g., French terms work best). It also clarifies the limit's role by explaining the lack of pagination, adding meaning 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 the tool searches recipes on Marmiton by free text with a specific verb and resource. It distinguishes from sibling tools by mentioning it returns IDs and URLs used by get_recipe, making its role as the search entry point explicit.

  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 provides clear context that Marmiton is a French site and advises using French terms. It explicitly explains the single-page limitation and advises narrowing queries instead of expecting pagination, effectively covering when and how to use the tool, though it 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.