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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is known. The description adds beyond that by specifying that it returns matching categories with red-flag counts and priority, and notes the Japan-specific nature. This gives the agent a clearer picture of the tool's output without contradicting annotations. A score of 4 acknowledges this added context.

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 two sentences (in both Japanese and English) that are front-loaded with the core purpose, followed by examples. There is no redundant filler, and the structure effectively conveys the key information in a compact form. Achieves a perfect score for conciseness and 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?

With only one parameter, no nested objects, and an existing output schema, the description is sufficiently complete. It covers the search behavior, examples, and return value highlights (red-flag counts and priority). The tool's simplicity and the presence of an output schema mean no additional context is necessary.

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?

The schema covers 100% of parameters with a simple description (工事名やキーワード), so baseline is 3. The description adds value by providing concrete example queries (外壁塗装, 浴室, 給湯器) and clarifying that Japanese keywords work best, which helps the agent form effective queries. This enrichment justifies one point above baseline.

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: 'Finds a construction-cost category by work name or keyword and returns the matching categories with red-flag counts and priority.' It uses a specific verb ('finds') and identifies the resource (construction-cost category) plus what it returns. It also gives concrete examples (外壁塗装, 浴室) that help distinguish it from siblings like list_cost_categories, which presumably lists all categories without a search query.

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: use this tool when you need to search by a work name or keyword rather than listing all categories. It provides examples of suitable queries and notes that Japanese queries work best, which gives practical guidance. However, it does not explicitly mention alternatives like list_cost_categories or state when NOT to use this tool, so it stops short of a perfect score.

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