analyze

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

With no annotations provided, the description fully handles behavioral disclosure: it explains the analysis process and classification logic. However, it omits details like error handling, performance, or whether it modifies files, which would be needed for a perfect score.

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 a clear introduction, bullet points for classifications, and an Args/Returns section. It is appropriately sized, though a slightly more concise phrasing could improve it.

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 is complete for a tool with no output schema: it details the return value (classified package list) and the three possible classifications, providing sufficient context for agent invocation.

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 provides clear semantics for all three parameters in the 'Args' section, explaining their purpose and defaults (e.g., max_depth default 10). This fully compensates for the 0% schema description coverage.

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 analyzes import graphs from an entry point and detects stubbable packages, with specific classification outcomes. This distinct purpose differentiates it from siblings like 'generate' or 'graph'.

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 implies usage by explaining classifications and recommending exclusions for nofollow packages, but does not explicitly state when to use this tool vs. alternatives or provide context for when not to use it.

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