recommend_temples

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

Discloses key behavioral trait (returned temples are scored/ranked) and natural language input capability beyond what annotations provide. No annotations exist to cover read-only status; description could clarify safety/permissions but 'recommend' implies read-only.

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?

Two tightly constructed sentences: first establishes purpose and method, second clarifies input flexibility. No redundancy or wasted words. Perfectly front-loaded.

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?

Appropriate for a 2-parameter tool with simple structure. Mentions scoring which hints at output format despite lacking output schema. Could explicitly mention return structure (list of temple objects with scores) for perfect completeness but adequate as-is.

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% with detailed examples in the query parameter. Description reinforces the free-form nature of input but adds minimal semantic detail beyond the schema's comprehensive examples. Baseline 3 appropriate for high coverage.

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?

Excellent specificity: states the tool recommends (スコア付きで推薦) Kyoto temples based on natural language queries. Distinguishes from sibling get_temple_detail by emphasizing recommendation/scoring behavior versus detail retrieval.

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?

Implies usage by describing flexible input options (traveler profiles, conditions) but lacks explicit guidance on when to use this versus get_temple_detail (e.g., 'use this for personalized recommendations, use get_temple_detail for specific temple facts').

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