quality_report

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

No annotations are provided, and the description does not detail behavioral traits such as performance impact, auth needs, or whether results are cached. A moderate score as it at least discloses the multi-category aggregation behavior.

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 a single dense sentence that efficiently conveys the tool's purpose and scope, with 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?

Given there is no output schema, the description could clarify the structure of the report (e.g., 'returns a JSON with per-category arrays'). However, it is sufficiently complete for a simple configuration like topN, and the parameter is well-covered by the schema.

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 parameter is fully documented. The description does not add extra meaning beyond the schema (e.g., what 'worst offenders' means or how topN affects output), so baseline 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 clearly states it returns a 'combined code quality report' covering complexity hotspots, coupled modules, and duplicate code. It distinguishes itself from sibling tools like detect_duplication and calculate_metrics by aggregating multiple categories in one call.

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 it is used for a consolidated overview of code quality issues, but does not explicitly state when to choose this over sibling tools like calculate_metrics or detect_duplication individually.

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