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

The description discloses the output format ('Returns titles, URLs and excerpts') and indicates it does not return full content by directing to get_article. However, it does not explicitly state that the operation is read-only or has no side effects, though this is implied by its nature.

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 succinct and well-structured: it states the purpose, lists topics, clarifies terminology, mentions return fields, and gives a follow-up instruction. Every sentence adds value without fluff.

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?

For a search tool, the description provides sufficient context: source domain, topic categories, term definitions, return format, and next step. It could mention pagination or sorting, but these are not critical for the tool's primary purpose.

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 description adds semantic meaning beyond the schema, particularly for the post_type parameter (defining 'column' and 'tech' orientations) and clarifies the scope of the query. This complements the schema descriptions, which are clear but laconic.

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 function: 'Search Japanese articles published on issoh.co.jp' with explicit topic coverage and clarification of the 'column' vs 'tech' distinction. This is a specific verb+resource+scope that effectively distinguishes it from other search tools.

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 provides a workflow hint ('Call get_article afterwards') but does not explicitly state when to use this tool over sibling search tools (search_case_studies, search_services). It implies usage based on the content type, but lacks direct comparative guidance.

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