analyze_coverage

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

With no annotations provided, the description carries the full burden. It discloses that the tool executes pytest with pytest-cov, parses coverage.json (never the human-readable summary), and computes overall coverage, per-file coverage, and uncovered line counts. This is comprehensive for a coverage analysis tool, though it could mention any destructive effects or file modifications.

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 at two sentences: the first line states the core purpose, and the second line details the execution and parsing behavior. Every sentence adds value 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?

Given that an output schema exists (so return values are documented separately), the description adequately covers the tool's behavior, parameters, and execution context. It could mention prerequisites like pytest-cov installation, but for a tool with good schema coverage and output schema, this is mostly sufficient.

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% coverage, so the baseline is 3. The description adds value by explaining that test_path restricts which tests to run and defaults to the whole suite, and repo_path must be under allowed roots. However, it does not elaborate on the parameters further beyond what the schema provides.

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 that this tool runs the test suite with coverage and reports real, per-file coverage numbers. It specifies the resource (test suite) and verb (analyze coverage), and the detail about parsing machine-readable coverage.json distinguishes it from any generic coverage tool.

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 clear context for when to use this tool (for running pytest with pytest-cov and getting machine-readable per-file coverage), but it does not explicitly say when not to use it or mention alternatives like detect_flaky_tests or record_test_run. It implies usage for coverage analysis among siblings focused on flaky detection, risk prediction, and history.

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