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

No annotations are provided, so the description carries the full burden. It discloses that the search is full-text, supports English and Korean, returns ranked matches with concept ids. However, it does not specify ranking criteria, case sensitivity, or wildcard support, leaving some behavioral aspects implicit.

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 extremely concise: two sentences that pack in the core purpose, domain context, language support, return format, and a clear next step. Every sentence earns its place with no extraneous information.

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 the absence of an output schema, the description adequately explains that the tool returns ranked matches with concept ids and directs to read_doc for full text. However, it does not mention whether the tags parameter affects the search or how ranking works, but the schema covers tags. Overall, it is mostly complete for a search tool with good schema coverage.

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 100%, so each parameter already has a description. The tool description does not add new parameter-level details beyond what is in the schema. The mention of language support aligns with the query parameter but does not enhance it. Baseline score of 3 is appropriate.

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 performs full-text search over a specific knowledge base, specifying the domains (AI-native development, agent/harness engineering, dev practice). It distinguishes itself from siblings by explicitly indicating that results are ranked matches with concept ids and directing the user to call read_doc for full text, which differentiates from list_topics.

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 clear next action (call read_doc with an id), but does not explicitly state when to use this tool versus its siblings (list_topics, read_doc). It implies that search is for finding relevant documents, but lacks explicit 'when to use' or 'when not to use' guidance.

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