cocotb_list_tests

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

No annotations are provided, so the description carries the behavioral disclosure burden. It does disclose the main guarantee ('without executing simulation') and the scope of results, which is helpful. However, it omits the return format, whether the file is parsed versus imported (potential module-level side effects), and error behavior, leaving meaningful gaps.

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 sentence states the operation, target, and key non-execution guarantee with no filler. Every word earns its place, 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?

For a simple two-parameter tool, the description plus 100% schema coverage is nearly sufficient: it states what the tool returns conceptually (test coroutines and docstrings) and that it does not run simulation. It is missing an explicit routing note to cocotb_run and a precise output format, but the remaining gaps are minor.

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 100%, so both test_file and cwd are already documented in the input schema. The description only reinforces that a Python testbench file is the target and adds no new parameter semantics, matching the baseline of 3.

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 uses a specific verb ('Discovers') and identifies the exact resource: all @cocotb.test() coroutines and their docstrings in a Python testbench file. The phrase 'without executing simulation' clearly separates it from siblings like cocotb_run, so an agent knows exactly what the tool does.

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 gives clear usage context: use it when you need to inspect test cases and docstrings without running simulation. It does not explicitly name the alternative tool or provide when-not-to-use guidance, so it earns a 4 rather than a 5.

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