Contributor Statistics

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

Annotations already declare readOnlyHint=true, covering the safety profile. The description adds an important behavioral prerequisite: the repo_path must be provided if the server was not started in a git repo. This goes beyond what annotations provide, though it doesn't describe return format or performance implications.

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 concise: two sentences plus a note. It front-loads the purpose, lists use cases efficiently, and ends with a critical usage note. No wasted words or 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 read-only analytics tool with no output schema, the description does a good job of conveying what the tool returns (active contributors, areas, commit patterns, collaboration graph). It also covers the repo_path requirement. It doesn't describe edge cases or output formatting, but for this level of complexity it's reasonably complete.

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 description coverage is 100%, so the baseline is 3. The description reinforces the repo_path requirement in the note but doesn't add significant extra meaning beyond what the schema already documents for days and author. It's adequate but not additive.

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: 'Comprehensive contributor analytics' and enumerates specific aspects (activity, areas, commit patterns, collaboration graph). It distinguishes from siblings like commit_patterns and churn through its broader scope, though it doesn't explicitly name alternatives.

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 provides concrete use cases: 'understanding team dynamics, identifying knowledge silos, onboarding planning, and workload distribution.' It gives clear context for when to use the tool but does not explicitly mention when not to use it or point to alternative sibling tools.

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