git:20260803.f52f41e to git:20260903.6713296

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name: api-test-pytest

description: Use this skill when you need to parse multi-format API definitions and generate Pytest API automation; triggers include Pytest API tests and API automation with Pytest.

---

# api-test-pytest (EN)

## When to Use

- Need API outputs that should land in pytest-based automation.

- The project is already Python-first or wants pytest-style structure.

## Workflow

1. Read and follow the main prompt listed under Progressive disclosure (coverage, structure, quality bar).

2. Add only project context that changes the result: scope, environment, constraints, risks, dependencies, expected deliverable.

3. If input is incomplete, return a usable first draft and explicitly mark assumptions and gaps.

4. Default to Markdown; switch formats only when the user asks.

## Core Constraints

- Prioritize by risk / business impact — do not treat everything equally.

- Separate confirmed facts from current assumptions.

- Do not invent endpoints, fields, environments, or root causes the user did not provide.

- Use placeholders or env-var semantics for auth/secrets; never hardcode real credentials.

- Keep output executable: concrete scenarios, clear priority, clear next steps.

## Progressive Disclosure

- Before producing output, read and follow `prompts/api-test-pytest.md` (minimum coverage, output structure, quality bar).

- When a ready-made template fits: use matching files under `output-templates/`.

- When the user wants examples or alignment with existing assets: read relevant `examples/`.

- For deep framework/troubleshoot/schema notes: read only the relevant file(s) under `references/`, do not load the whole directory.

- For format conversion or helper checks: prefer existing `scripts/` over reinventing.

- For evaluating/regressing this skill: use `evals/` with skill-up.

## Pre-delivery Checklist

- [ ] Followed the main prompt's output structure

- [ ] Minimum coverage focus: module structure, fixture strategy, auth handling, priority endpoints, positive scenarios, negative and boundary scenarios, assertion focus, test data strategy, ... (details in main prompt)

- [ ] Covered the minimum checklist, or explained omissions

- [ ] High-risk items have explicit priority

- [ ] Did not invent details the user did not provide

- [ ] Assumptions and gaps are marked

## Common Pitfalls

- Do not pretend completeness when scope/context is missing.

- Do not treat every item as equally important.

- Do not skip assumptions and information gaps.

- Do not dump generic theory unrelated to the current toolchain.