Git Analytics MCP Server

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It describes a read operation ('get') but doesn't mention performance characteristics, rate limits, authentication needs, or what 'detailed statistics' entails in terms of output format or data scope. This leaves significant gaps for an agent to understand how the tool behaves beyond its basic function.

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, efficient sentence that front-loads the core purpose. It avoids redundancy and wastes no words, though it could be slightly more structured by separating purpose from scope details.

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's complexity (statistical analysis with no output schema) and lack of annotations, the description is incomplete. It doesn't explain what 'detailed statistics' includes, how data is aggregated, or the return format. For a tool with behavioral unknowns and no structured output documentation, this leaves the agent under-informed.

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 has 100% description coverage, with the single parameter 'path' well-documented in the schema. The description adds no parameter-specific information beyond what the schema provides, so it meets the baseline of 3 for high schema coverage without compensating value.

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 specific verbs ('get detailed statistics') and resources ('contributors'), including what statistics are retrieved ('commits, code changes, and activity periods'). It distinguishes itself from siblings by focusing on author-level data rather than repository-level overviews or general statistics, though it doesn't explicitly name the sibling tools.

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 no guidance on when to use this tool versus the sibling tools (get_repository_overview, get_repository_stats). It mentions 'contributors' which implies author-focused analysis, but doesn't specify use cases, prerequisites, or exclusions. The agent must infer usage from the purpose alone.

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