Contributor Statistics

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

Annotations already declare readOnlyHint=true, so the description doesn't need to restate safety. It adds value by detailing the scope of analytics and the collaboration graph aspect. No contradictions.

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 plus a note, front-loaded with purpose. Every sentence earns its place without redundancy.

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?

For a tool with 3 simple params, no output schema, and good annotations, the description covers purpose, usage, and a key prerequisite. Missing return format details but acceptable given no output 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?

All 3 parameters are described in the schema (100% coverage). The description adds a redundant note about repo_path but doesn't clarify days or author beyond schema defaults. 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 provides 'comprehensive contributor analytics' including specific aspects like activity, areas, commit patterns, and collaboration graph. It effectively distinguishes from sibling tools (e.g., hotspots, churn) by focusing on people rather than code or risk.

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 explicitly states when to use this tool (understanding team dynamics, knowledge silos, onboarding, workload distribution) and provides a critical prerequisite note about repo_path if not in a git repo. No exclusions, but the context is clear.

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