query_knowledge_base

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

With no annotations, the description carries the transparency burden. It discloses the matching approach (fuzzy keyword), return count (top-3 default), and returned fields. It does not explicitly state it is read-only, but the query nature implies no side effects. This is sufficient for a simple query tool.

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 three concise sentences, each carrying essential information. It front-loads the main purpose and efficiently covers behavior and output. No unnecessary 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?

For a simple query tool with full parameter schema, the description is mostly complete. It explains what the tool does and what it returns. However, it could be slightly more explicit about the output format (e.g., list of objects with the specified fields) since no output schema exists.

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 baseline is 3. The description adds no new parameter information beyond what the schema provides, but it reinforces the default for top_n. No additional meaning or constraints are contributed.

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: consulting a knowledge base to find similar solutions using fuzzy keyword matching. It specifies the resource, the matching method, and the return fields (confidence, reuse count). This distinguishes it from sibling tools like 'show_knowledge' which likely displays all entries.

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 when needing to find similar solutions, but lacks explicit guidance on when to use this tool versus alternatives. No exclusion criteria or comparative direction is provided.

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