api-test-pytest (EN) - QA Skill Library

Why this Skill

It turns this Skill's method into a quality input that can be executed, reviewed, and reused.

Need API outputs that should land in pytest-based automation.
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.
Do not pretend completeness when scope/context is missing.

When to use

Use this Skill

Need API outputs that should land in pytest-based automation.
The project is already Python-first or wants pytest-style structure.

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.

Input

Minimum Input

The current task scope, objective, and subject under review.

Recommended Input

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.

Optional Context

For format conversion or helper checks: prefer existing scripts/ over reinventing.
For evaluating/regressing this skill: use evals/ with skill-up.

Output

The output follows this Skill's method and makes facts, assumptions, risks, and next steps explicit.

Judge the output value before installing

01Followed the main prompt's output structure
02Minimum 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)
03Covered the minimum checklist, or explained omissions
04High-risk items have explicit priority

View full output structure

05Did not invent details the user did not provide
06Assumptions and gaps are marked

How It Works

01Read and follow the main prompt listed under Progressive disclosure (coverage, structure, quality bar).
02Add only project context that changes the result: scope, environment, constraints, risks, dependencies, expected deliverable.
03If input is incomplete, return a usable first draft and explicitly mark assumptions and gaps.
04Default to Markdown; switch formats only when the user asks.

Install & Quick Start

Install command / SHELL

npx skills add \
  https://github.com/naodeng/awesome-qa-skills/tree/main/skills/en/testing-types/api-test-pytest
  -g

api-test-pytest.prompt

@skill api-test-pytest

Using the current project context, produce an actionable result following this Skill.

Additional context:
[Paste project context or requirement]

---
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)

**Chinese version：** See the corresponding Chinese skill.

## 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.