Internal Documentation Search

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 describes the search behavior and return format (JSON string with matching documents or not-found message), which is helpful. However, it doesn't disclose important behavioral traits like whether this is a read-only operation, if there are rate limits, authentication requirements, or how results are ranked/limited.

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 well-structured and appropriately sized. It starts with the core purpose, provides usage guidelines with bullet points, then documents parameters clearly, and ends with return information. Every sentence earns its place with 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 the tool's moderate complexity (3 parameters, search functionality) and the presence of an output schema (which handles return values), the description is quite complete. It covers purpose, usage guidelines, and parameter semantics effectively. The main gap is the lack of behavioral transparency details that would be important for a search tool (like rate limits or result limits).

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?

With 0% schema description coverage, the description must compensate for the lack of schema documentation. It successfully explains all three parameters: query (free-text search), category (optional filter with valid values), and tags (optional list filter with examples). This adds substantial meaning beyond the bare schema, though it doesn't specify exact format requirements for tags.

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 an internal knowledge base for specific document types (standards, runbooks, architecture decisions). It uses the specific verb 'search' with the resource 'internal knowledge base' and distinguishes itself from siblings by focusing on search functionality rather than retrieval or listing operations.

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 explicit guidance on when to use this tool with three concrete examples (engineer asks about how something should be done, incident response, or architectural choices). It distinguishes this search tool from siblings like get_document (likely for retrieving specific documents) and list_all_docs (likely for listing without search).

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