Analyze Methods

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

Annotations already indicate this is read-only and idempotent. The description adds value by detailing what analysis is performed (parameters, decorators, complexity, data flow), which goes beyond annotations. No contradictions.

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 extremely concise: a one-line summary followed by organized Args and Returns sections. Every sentence is informative and earns its place.

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 (method analysis), the description is fairly complete. It covers inputs, optional filter, and output. However, it does not mention performance considerations for large files, which would be helpful.

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%, so the description adds minimal extra beyond the schema. It repeats parameter descriptions but does not provide deeper semantics like file size limits or encoding requirements.

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 detailed method analysis of a Python file, listing what is returned (methods with parameters, decorators, complexity, data flow). It is distinct from sibling tools like cc_analyze_code and cc_extract_classes.

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 includes explicit parameters (path and optional class_name) and the return format, but lacks guidance on when to use this tool versus alternatives like cc_analyze_code or cc_extract_classes. It is clear but does not exclude other tools.

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