code_graph_search

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

With no annotations provided, the description carries the full burden. It does add valuable behavioral traits: it explicitly labels the operation as read-only and outlines the fuzzy matching algorithm. However, it omits details about return format, pagination behavior, or what happens with empty results, so transparency is partial but not nil.

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 brief and front-loaded with the core purpose. It packs essential details (search order, filter usage, read-only nature) into two sentences without redundancy. Every clause earns its place, making it highly concise and well-structured.

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 has 5 parameters, no output schema, and no annotations, the description is too thin. It fails to explain key parameters like app_id and db_path, does not describe what the tool returns (e.g., list of symbol matches, paths, or metadata), and lacks guidance on max_results. An agent would struggle to invoke it correctly without additional context.

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 0%, so the description must compensate for all parameters. It only explains 'kinds' with its allowed values (module|class|function|method). It does not explain 'query', 'app_id', 'db_path', or 'max_results', leaving their semantics to the agent's inference. This is insufficient given the complete lack of schema descriptions.

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 fuzzy symbol search over a code graph, with a specific verb ('search') and resource ('graph'). It distinguishes from sibling tools like code_graph_explain or code_graph_walk by focusing on search, and even details the search order (exact → prefix → contains → token split). This is unambiguous and specific.

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 for finding symbols in the code graph but does not explicitly state when to use this tool versus alternatives like code_graph_suggest or knowledge_search. It mentions optional 'kinds' filtering but provides no scenarios or exclusions. The guidance is only implicit through the search-focused wording.

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