get_coverage

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

No annotations provided, so description carries full burden. It explains return values (counts, percentage, skip reasons) and implies it is a read-only check. However, it does not disclose prerequisites (e.g., must have run analyze_project) or potential performance costs.

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?

Description is concise, with a clear two-sentence purpose, bullet-like use cases, and a return summary. Every sentence adds value.

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 covers the main purpose, usage context, and return values. It is almost complete, though it could mention default values for path or depth limits.

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%, and the description does not add much beyond the schema descriptions for path and depth. The baseline 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?

Description clearly states it checks which files were analyzed/skipped, with specific use cases like finding gaps, verifying patterns, and debugging empty results. It distinguishes itself from siblings like analyze_project by being a post-analysis diagnostic tool.

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 states to use AFTER analyze_project when queries return unexpected empty results, and lists four specific scenarios. No explicit when-not-to-use, but the context is clear and helpful.

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