search_knowledge_base

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

Annotations already declare readOnlyHint/idempotentHint/destructiveHint=false, so safety is covered. The description adds genuine value beyond that: the retrieval pipeline (BM25 + embeddings + reranker) and the exact shape of results (path, line range, GitHub permalink, chunk text). Auth/rate-limit behavior is not mentioned, keeping it short of a 5.

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?

Three sentences, front-loaded with the retrieval mechanism, then usage, then parameter guidance. No filler; each sentence adds distinct 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?

An output schema exists, so return values need not be spelled out, yet the description usefully summarizes them. The one gap is the unresolved relationship with ask_knowledge_base, leaving the agent to infer which retrieval tool fits a given question.

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 coverage is 0%, so the description must carry the load, and it does: "top-k chunks" explains the purpose of k, and "Write the query the way the answer would be phrased, and include exact identifiers" is concrete guidance for the required query parameter. It stops short of documenting k's default/range explicitly.

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?

States a specific verb+resource (hybrid BM25/embeddings/reranker search over indexed repository docs and code) and names the mechanism, so an agent can tell it apart from read_file and list_sources without opening a schema. The scope (repository docs and code) is explicit.

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?

"Use for any question about how our code or documentation works" gives clear context, and the query-phrasing tip tells the agent how to drive it. It does not, however, resolve when to prefer this over the sibling ask_knowledge_base, and gives no exclusions. Clear context without alternatives.

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