list_tests

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

With no annotations, the description fully carries the burden. It details the underlying commands per framework (e.g., pytest --collect-only) and the return format (list of nodeid/filename). It could mention that the tool is read-only and safe to run, but overall it is transparent.

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 and well-structured: first sentence lists mechanisms for each framework, second sentence describes the return format, and third provides usage guidance. No extraneous information.

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 no output schema, the description explains the return format (list of nodeid/filename). It is complete enough for a listing tool, though it could mention potential performance impacts for large projects. Overall, it provides sufficient context.

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?

There are zero parameters, and schema coverage is 100% (trivially). The description adds no parameter-level details because none are needed, but it does explain the tool's behavior without relying on params. Baseline 4 is appropriate.

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 lists all executable tests using native collection mechanisms for multiple frameworks (pytest, Jest, Cypress, Go, Maestro). It distinguishes itself from sibling tools like run_tests (execution) and generate_test (creation) by specifying its purpose.

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 explicit usage scenarios: before run_tests to confirm coverage and before generate_test to avoid duplicates. It gives clear context but does not explicitly mention when not to use the tool.

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