kaken_search_projects

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

With no annotations, the description carries the full burden. It states the output format (compressed Markdown with specific fields) and mentions that results include project number, representative, affiliation, etc. It implies a read-only search operation. However, it does not disclose potential rate limits, authentication requirements, or pagination behavior beyond the start parameter. The behavioral transparency is good but not exhaustive.

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 paragraph that front-loads the tool's purpose and use cases. It is moderately sized (about 100 characters) and every sentence adds value. It could be slightly more structured (e.g., bullet points for use cases), but it is concise and avoids redundancy.

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 18 parameters and no output schema, the description covers the tool's purpose, use cases, and output format. However, it does not explain pagination details (e.g., how start and rw interact) or mention the output format parameter (format: ai/table/json) beyond the default. The lack of an output schema increases the need for the description to explain return values, but it only briefly mentions the Markdown content. Some completeness gaps exist.

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 94%, so the baseline is 3. The description adds some value by grouping parameters (e.g., 'フリーワード(kw)・課題名(qa)・分野(qd)・機関(qe)・年度(s1/s2)') and stating they can be combined. However, it does not provide additional semantics beyond what the schema already explains for most parameters. Since coverage is high, the description's contribution is minimal.

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 searches the KAKEN database for research projects, lists specific use cases (competitor/prior research, trend grasp, reference data collection), and distinguishes itself from sibling tools like kaken_get_project (which retrieves a single project) and kaken_search_researchers (which searches researchers). The verb 'search' combined with the resource 'projects' and the detailed usage scenarios provide high-purpose clarity.

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 explicitly provides usage scenarios (競合・先行研究調査、特定分野の採択動向把握、申請書作成時の参考データ収集) and mentions combining parameters. However, it does not explicitly state when not to use this tool versus alternatives (e.g., when to use kaken_get_project instead). The context is clear but lacks exclusion criteria.

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