check_registered_use

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

With no annotations, the description carries full behavioral transparency burden. It discloses that output candidates include 'match_confidence' and 'matched_fields', and that it never returns fields like 'allowed'. This informs the agent about the non-deterministic, confidence-based nature of results. It also warns to check product labels, adding safety context. No contradictions with absent annotations.

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 concise (4 sentences) and front-loaded with the primary purpose. Every sentence adds unique value: core function, output fields, what it does not return, and a safety warning. No wasted words.

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 5 parameters, no output schema, and 0% schema description coverage, the description is incomplete. It fails to explain parameter meanings, expected values, or constraints. It mentions output fields but not the full return structure. A more complete description would clarify parameter usage and return format.

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 has 0% description coverage for 5 parameters. The description provides no explanation of any parameter (crop, pest, limit, usage_method, pesticide_name_or_register_no). The agent must infer semantics solely from parameter names, which is insufficient. The description does not compensate for the lack of schema descriptions.

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 returns 'candidates of registration rows' matching conditions, using a specific verb ('返す' - returns) and resource ('登録行の候補'). It explicitly distinguishes from sibling tools by clarifying it is not a usability judgment, and the sibling tools (e.g., get_applications, search_pesticides) have different purposes.

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 context by stating it is not a usability judgment, suggesting the tool is for exploratory candidate retrieval rather than definitive answers. However, it does not explicitly state when to use this tool vs. siblings, nor provide when-not-to-use or alternatives. The warning to verify before actual use is a post-hoc guideline.

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