structure

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

With no annotations, the description carries the full burden and excels: it discloses determinism, current-code snapshot, cost considerations for detail levels, and even flags that the `doc` field is unverified author intent. This is exemplary 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 single-paragraph description is dense yet readable, with every clause adding concrete value—no filler or repetition. It front-loads the core purpose before diving into parameter trade-offs.

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's complexity and rich enum parameter, the description covers all necessary operational context: what is returned per detail level, how to use paths, cost implications, and a caveat about data reliability. Without an output schema, this description fully compensates.

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%, but the description adds substantial value beyond the schema by explaining each detail level's content, token costs, and when to avoid hashes. It also clarifies the `doc` field's caveat, which is critical for correct interpretation.

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 returns the deterministic structure (files + symbols) of an enrolled repo's current code, with a specific use case: grounding claims about functions/types/exports. It distinguishes itself from sibling tools by focusing on structural inspection rather than diffs, hashes, or status.

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?

Explicit guidance is given for when to use the tool ('to ground claims about what functions/types/exports exist') and how to scope it with paths and detail levels. It does not explicitly mention alternatives, but the strong purpose statement effectively differentiates it from siblings.

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