Discover the Python automation project

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

The annotations already declare readOnlyHint, idempotentHint, and destructiveHint false, and the description enriches this substantially: it promises no execution or imports, reads config files as text, exposes the partialSuccess status semantics ('not found' may mean 'not looked at'), and states that every conclusion carries signals and an explicit confidence level. It also says it makes no folder-layout assumptions and is 'always safe to repeat,' which is consistent with the idempotent annotation.

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 long but well structured and front-loaded with the main purpose. Each listed artifact and caveat adds meaningful guidance, and the critical call-time directive is placed near the end. It is slightly dense and has minor redundancy around read-only/safe-to-repeat, but every sentence contributes to agent understanding.

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 this is a zero-parameter tool with a rich output schema, the description is complete: it explains what will be discovered, how conclusions are evidenced, the no-execution guarantee, the partialSuccess edge case, when to call it, and its safety profile. Nothing an agent needs to decide whether and when to invoke this tool is missing.

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 tool has zero parameters and the schema coverage is 100%, so there are no parameter semantics for the description to clarify. Per the rubric, zero params yields a baseline of 4. The description instead focuses on behavior and outputs, which 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 opens with a specific verb and resource: 'Scan the configured workspace and report the Python automation project that is actually there.' It enumerates concrete artifacts and properties (pyproject.toml, lock files, test runner, virtual environments, browser library, page-object directories, CI config) and clearly separates this discovery tool from the only sibling, genxevo_agent_status, by adding a directive: 'Call this before reasoning about any test, locator or run.'

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 an explicit invocation point: 'Call this before reasoning about any test, locator or run.' It also states what the tool will not do, e.g., it never imports or executes project code, and it reads setup.py/conftest.py as text only. It does not name exclusions or explicitly compare against genxevo_agent_status, but for a zero-parameter discovery tool the guidance is clear enough.

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