check_documentation_coverage

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

With no annotations, the description carries full behavioral burden. It discloses that the output includes both scoped coverage and model-wide coverage, and explains the denominator logic and the legacy behavior of the 'all' scope. It doesn't mention side effects (none expected for a read operation) but adequately describes the behavior.

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, front-loaded with the core purpose, and uses a bullet list to explain the parameter without wasted words. Each sentence adds value, and the structure is easy to scan.

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?

The description explains the output fields (coverage and coverageModelWide) and the parameter options, which is sufficient for an agent to call it correctly. The presence of an output schema covers the exact return structure, and the description adds the meaningful semantic details.

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 zero description coverage for the 'scope' parameter, so the description fully compensates. It defines the parameter's meaning (controls the denominator), lists the two valid values with explicit effects, and explains the default. This is comprehensive.

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 returns the fraction of named elements with documentation set, using a specific verb and resource. It distinguishes itself from siblings like check_requirement_coverage (requirements vs documentation) and get_model_metrics (general metrics) by specifying its exact metric.

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?

It explains the scope parameter choices and the rationale for the default ('authored' avoids the ~25% ceiling), which guides when to use which scope. However, it does not explicitly contrast with alternatives like check_requirement_coverage or get_model_metrics, so the guidance is limited to the scope parameter.

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