quality_hotspot_detectionIdentify files with the highest defect density to focus testing and code review efforts on the most critical code areas.
Identify files with the highest defect density (hotspots).
| Name | Required | Description | Default |
|---|---|---|---|
| github_ref | Yes | GitHub 'owner/repo' reference |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It only restates the core purpose and does not communicate any behavioral traits such as read-only status, computational approach, prerequisites, or limitations. An agent has no sense of what side effects or guarantees to expect.
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, focused sentence with no superfluous content. It is front-loaded with the core action and resource, making it easy for an agent to parse quickly.
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 tool is simple: one required, fully documented parameter and an output schema is present, so return-value details need not be in the description. The main gap is the lack of usage guidance, but the invocation surface itself is adequately covered for a straightforward analysis tool.
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 input schema already provides 100% coverage for the single parameter github_ref, so the description does not need to add parameter details. It adds no extra semantic meaning beyond the schema, which aligns with the baseline score of 3.
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 uses a specific verb ('Identify') and a clear resource ('files with the highest defect density'), immediately conveying the tool's unique purpose. It distinguishes itself from siblings like analyze_code_quality or defect_trend_analysis by focusing specifically on defect-dense hotspot files.
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?
No guidance is given about when to use this tool versus alternatives such as analyze_code_quality or defect_trend_analysis. The description provides no context, exclusions, or decision criteria for an agent to select this tool over its siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.