Language Statistics

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

Annotations already denote readOnly and idempotent behavior. The description adds 'bounded line counting' and 'primary-language detection,' which are useful behavioral details beyond what annotations provide. No contradiction with annotations.

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?

A single, efficient sentence that conveys the core functionality with no redundancy. Every word earns its place.

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 presence of an output schema, the description does not need to detail return values. It covers the main outputs (file count, line count, primary language). However, it omits context about the path parameter's restrictions (from schema) and the numeric bounds, which are relevant for usage.

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 only 33%; only 'path' is described. The description adds no parameter-level information. For the three parameters, the description does not compensate, leaving interpretation heavily reliant on the schema.

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 language breakdown by file count and line counting, plus primary-language detection. This is specific and distinguishes it from sibling tools that perform different analyses like repository snapshot or code search.

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 on when to use this tool versus alternatives. It simply states what it does, leaving the agent to infer from context. Lacks explicit when-to-use or when-not-to-use information.

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