search_code

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

With no annotations, the description carries the burden. It discloses the search algorithm (BM25), return fields (snippets, line numbers, relevance scores), and scope (all indexed code chunks). Missing details like auth, rate limits, or performance are acceptable for a non-destructive search 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 two sentences, front-loaded with purpose and return type, then usage guidance. Every sentence adds value 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 no output schema, the description compensates by mentioning return fields. It covers the algorithm, scope, and use context. Could be more complete (e.g., ordering, case sensitivity) but is sufficient for a simple search tool with 2 parameters.

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 100% as both parameters have descriptions. The tool description adds no extra meaning beyond the schema for parameters, so the baseline 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 a lexical BM25 search across all indexed code chunks, returns snippet matches, line numbers, and relevance scores, and positions itself as best for general code search. This distinguishes it from sibling tools like semantic_search or regex_search.

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 phrase 'Best for general code search' provides implicit guidance on when to use this tool over more specific search tools (e.g., regex, semantic). However, it lacks explicit when-not-to-use or direct alternative mentions.

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