auto_generate_tests

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

No annotations are provided, so the description carries the full burden. It describes the internal steps (analyze_url, generate_test per module, writing to PROJECT_ROOT/tests/), how candidate_tcs become docstrings, and the return value. It also notes that setting tests_per_module to 10 usually produces garbage tests, offering caution.

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 well-structured: first states purpose, explains equivalence to manual steps, details docstring usage, and then covers parameters and defaults. Every sentence is informative with no 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 no output schema, the description explains the return value (list of file paths + counts per module). It covers input parameters and the overall process well, though it could be more explicit about error handling for steps like analyze_url failure.

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 coverage is 100%, but the description adds significant value by providing usage details: url must include protocol, timeout_ms default and suggestion for slow sites, auth_cookie format and source, and tests_per_module range and effect on test quality.

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 automates the sequence of analyze_url followed by generate_test for each detected module, writing pytest files. It distinguishes itself from sibling tools like generate_test (single test) and analyze_url (analysis only) by being a one-click batch automation for quick coverage.

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 specifies that it's suitable for 'give me a URL, you handle the rest' quick coverage scenarios, implying use when full automation is desired. It does not explicitly state when not to use it, but the context is clear enough.

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