extract_pytest

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

Annotations are all false and provide no safety profile, so the description carries the full burden. It says only what evidence is extracted, not whether the tool writes to an evidence store, whether it is idempotent, whether auth is needed, or whether existing extractions are affected.

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 front-loaded sentence with no filler; the evidence categories are compactly enumerated. Every word contributes to defining what the tool extracts.

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?

With one required parameter and an output schema, the description is minimally adequate: it identifies the input kind and the evidence variety. However, it lacks workflow context, preconditions, and side-effect information, so it is not fully complete.

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 0% and the description does not mention run_id at all. The parameter name is self-descriptive as a run identifier, but the description adds no guidance about where the id comes from, its format, or what conditions must hold for the run to be valid.

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 names a specific verb ('Extract') and a concrete resource domain ('pytest') with five concrete evidence categories, so an agent can tell it apart from sibling extract_* tools by domain. It doesn't name the source artifact or a direct sibling, but the pytest scoping makes the purpose clear.

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 phrasing implies this tool is for pytest-specific evidence and is the natural choice when that evidence is needed. However, there is no explicit when-to-use guidance, no preconditions, and no contrast with other extract_* siblings.

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