edge_quality_report

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

No annotations provided, so description carries full burden. The description implies a read-only audit (no destructive hints), but does not explicitly state it is non-mutating or mention any side effects. However, the behavioral details given (outputs) are sufficient for safe invocation.

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?

Two concise sentences: first states action and output, second states usefulness. No wasted words, front-loaded with key information.

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 lacking an output schema, the description fully covers return values (counts, avg confidence, top-10 edges). Parameters are well-documented in schema. All necessary context for confident usage is provided.

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?

Input schema has 100% description coverage, with each parameter (project, agent_id, session_id) clearly explained. The description adds no additional meaning beyond the schema, so 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?

Description clearly states the tool audits edge quality, lists specific outputs (counts, avg confidence, top-10 edges), and explicitly differentiates its diagnostic purpose (e.g., identifying noisy RELATES_TO edges) from sibling tools like get_stats or fsck.

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?

Describes when to use it ('diagnosing graph health'), but does not explicitly mention when not to use it or alternatives. Still provides clear context for usage.

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