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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.

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.

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.

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.

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.

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.