contributor_impact_analysis

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

With no annotations, the description carries the transparency burden. 'Analyze' implies read-only behavior, and the return type is stated ('Contributor impact analysis with expertise areas'), but it does not explicitly confirm that no modifications are made, nor does it mention potential side effects like repository access costs or permissions. This is adequate but not thorough.

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: a clear purpose statement, an Args section with one-line explanations, and a Returns section. No redundant or filler content; 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?

Given the tool has 4 parameters, no output schema, and no annotations, the description covers the essential aspects: what it does, each parameter's meaning, and the type of return value. It lacks examples or edge-case guidance, but is sufficiently complete for an agent to understand and invoke the 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 schema has 0% description coverage, forcing the description to explain each parameter. The 'Args:' section provides concise, meaningful descriptions for all four parameters (repo_path, days_back, min_commits, focus_on_important_modules), fully compensating for the schema's lack of detail.

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 the tool's purpose with a specific verb ('Analyze') and resource ('contributor patterns and their impact on important modules'), and additionally identifies key contributors and areas of expertise. This distinguishes it from siblings like coderank_analysis or get_commit_hotspots, which focus on code metrics rather than contributor attribution.

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 usage for analyzing contributor patterns and impact, providing clear context. However, it does not explicitly state when to prefer this tool over alternatives or mention exclusions, so it misses the top score but remains clearly contextual.

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