overview

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

No annotations provided, but description discloses output content (project type, languages, complex files, dependencies, circular import warnings), token estimate (~500), and format options. It implies read-only behavior without side effects.

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?

Two sentences for purpose, then parameter descriptions in a clean bullet-like format. No redundancies, front-loaded with key 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?

Given the tool's simplicity (3 parameters, output schema exists), the description covers all needed aspects: what it does, parameters, output hints, and next-step guidance. Nothing critical missing.

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?

All three parameters have meaningful descriptions: repo_path with example, exclude_dirs with format and example, output_format with default and option. Schema coverage is 0%, so 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?

Clearly states the tool provides repo orientation (project type, languages, files, dependencies, warnings) and distinguishes from siblings like prepare_context by guiding the agent to use it for understanding structure and then call prepare_context for coding tasks.

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?

Explicitly says when to use (understand codebase structure) and when not (for coding tasks, use prepare_context instead) with a clear alternative mentioned.

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