analyze_file

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

With no annotations, the description is the sole source of behavioral info. It explains what the tool lists and includes line numbers, but it does not disclose potential limitations (e.g., handling of malformed files) or explicitly confirm read-only behavior. Adequate but not detailed.

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 concise and front-loaded. It begins with the primary purpose, then details the contents, then gives usage guidance and the parameter description. Every sentence contributes useful information without redundancy.

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 presence of an output schema (which likely describes return values) and only one parameter, the description sufficiently covers purpose, usage context, and parameter semantics. It does not address error handling or edge cases, but for a high-level analysis tool this is acceptable.

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 input schema provides no description for 'path' (0% coverage), but the description compensates with an Args section: 'path: Path to a .py file.' This clarifies the expected type and format, adding meaning beyond the bare schema property.

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 function: 'High-level summary of every symbol in a Python file.' It enumerates specific symbol categories (classes, functions, async functions, methods, module-level assignments), which distinguishes it from sibling tools that focus on individual symbol types.

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 explicitly advises 'Start here when exploring an unfamiliar module,' which establishes a clear use case. It does not explicitly mention alternatives or exclusions, but the guidance is strong enough to indicate when to use this tool.

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