marm_code_lookup

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

Without annotations, the description carries the full burden. It discloses that the tool returns a 'graph lookup response, or a graph-unavailable error if the graph backend is disabled or failed to start.' It also explains the behavior of kind=auto based on query type. However, it does not detail the structure of the response or mention any authentication or rate limits, which would improve transparency.

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 with an emoji, bolded key terms, a concise overview, and a bulleted parameter list. Every sentence adds value, and the length is appropriate for the complexity of the tool. It is front-loaded with the most important 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?

The description effectively explains the tool's functionality and parameters, and it mentions the return type. Given the complexity (6 parameters, no output schema, no annotations, and many sibling tools), it is largely complete. However, it could briefly mention what a 'graph lookup response' contains or provide an example to further aid understanding.

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?

The description adds significant meaning beyond the input schema. For each parameter, it explains its purpose and behavior: e.g., query can be 'symbol name, natural-language phrase, code/text pattern, or a qualified_name'; kind options are detailed; regex is for text search; project can be omitted for auto-resolve; file_pattern is a glob. With 0% schema coverage, the description fully compensates.

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: 'Find code: symbols/definitions, text patterns, or a symbol's source.' It distinguishes itself by saying 'Use INSTEAD OF grep/glob,' and explains the different modes (auto, symbol, text, snippet), making it easy to understand what the tool does and how it differs from siblings.

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 and its alternatives: 'Use INSTEAD OF grep/glob.' It also explains the behavior of each kind value, e.g., 'kind=auto picks: a qualified_name reads source; otherwise it searches the graph by name/keyword. Set kind=text to grep code, kind=snippet to read a symbol's source, kind=symbol to force graph search.' This gives clear context for selecting the appropriate mode.

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