mcp_howtocook_getRecipeById

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

No annotations are provided, so the description carries the full burden. It mentions the tool returns '完整详情' (complete details) including ingredients and steps, which adds some behavioral context. However, it doesn't disclose critical traits like whether this is a read-only operation, error handling for invalid queries, performance expectations, or authentication needs, leaving significant gaps 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.

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

The description is a single, efficient sentence that front-loads the core purpose. It avoids unnecessary words and directly states what the tool does. However, it could be slightly more structured by separating usage context from behavioral details to improve clarity.

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 no annotations and no output schema, the description is moderately complete for a simple lookup tool. It covers the purpose and parameter basics but lacks details on return format, error conditions, or performance limits. For a tool with one parameter and 100% schema coverage, it's adequate but leaves room for improvement in behavioral transparency.

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 description coverage is 100%, with the parameter 'query' documented as supporting recipe names or IDs with fuzzy matching. The description adds minimal value beyond the schema by restating that it queries by '菜谱名称或ID' (recipe name or ID) but doesn't provide additional syntax, format examples, or clarification on how fuzzy matching works. Baseline 3 is appropriate given the schema does the heavy lifting.

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 the tool's purpose: '查询指定菜谱的完整详情' (query for complete recipe details) with specific resources (ingredients, steps). It distinguishes from sibling tools by focusing on individual recipe lookup rather than listing all recipes, filtering by category, or providing recommendations. However, it doesn't explicitly name the sibling tools for differentiation.

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?

The description implies usage when needing complete details for a specific recipe identified by name or ID, which contrasts with sibling tools for bulk retrieval or recommendations. However, it lacks explicit guidance on when to use this tool versus alternatives like 'getRecipesByCategory' for category-based filtering or explicit exclusion criteria.

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