analyze_summary

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

No annotations exist, so the description carries full burden. It discloses that only static imports are considered and dynamic imports are filtered, which is a critical behavioral detail. However, it does not mention mutability, authentication needs, or performance implications.

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 sections (purpose, returns, use when, important, example). It is concise, front-loaded, and every sentence adds value. No wasted words.

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?

Despite no output schema, the description explicitly lists the return fields with an example. It covers purpose, usage, and limitations. Given the tool's simplicity and the presence of well-named siblings, the description is complete for an agent to decide and invoke correctly.

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% with a single parameter (min_dependents) that has a clear description. The description does not add extra meaning beyond the schema, so a baseline score of 3 is appropriate.

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 states 'Get a summary of all dependency analyses' and lists specific return fields (circular_dependencies, hotspots, etc.), clearly identifying it as an overview tool. It distinguishes from siblings like find_circular, find_hotspots, etc., which are detailed analysis tools.

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 'Use this when' section explicitly guides the agent: quick health check, understanding structure, deciding next analysis. The IMPORTANT note provides a key constraint. No explicit when-not-to-use or alternatives listed, but the context is clear.

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