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Agent skill

Python Testing

by HoangNguyen0403 in HoangNguyen0403/agent-skills-standard

Test Python services with pytest, async coverage, monkeypatch, and boundary-focused fakes.

MITAuto-check passedTesting & QA

Install Python Testing

skills CLI
$ npx skills add HoangNguyen0403/agent-skills-standard --skill python-testing -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install HoangNguyen0403/agent-skills-standard python-testing --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/HoangNguyen0403/agent-skills-standard.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/python/python-testing .claude/skills/python-testing && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
python-testing
GitHub stars
570
Token cost
~851 tokens
SKILL.md length
354 words
Files
3 (incl. references)
Skills in repo
218
Repo updated
First seen
Licence
MIT

At a glance

Test Python services with pytest, async coverage, monkeypatch, and boundary-focused fakes.

  • Works in 5 steps: Write the failing test first for the… → Patch one seam high enough to keep the… → Assert structured outcomes: metadata,… → …
  • Writing Python tests
  • SKILL.md covers Priority: P0 (CRITICAL), Core Rule Anchors, Rules and Recipe, plus 2 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Python Testing is an agent skill from HoangNguyen0403/agent-skills-standard. Test Python services with pytest, async coverage, monkeypatch, and boundary-focused fakes. Use when writing Python tests, fixtures, async tests, regression tests, or dependency-isolated verification.

Its SKILL.md is about 850 tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files (for example `evals/evals.json` and `references/pytest-patterns.md`).

It sits in Testing & QA, covering Unit testing. It works with Python and pytest. The repository describes itself as: A collection of Agent Skills Standard and Best Practice for Programming Languages, Frameworks that help our AI Agent follow best practies on frameworks and programming laguages. The licence is MIT.

When your agent uses it

  • Writing Python tests
  • Regression tests
  • Dependency-isolated verification

Example prompts

  • “/python-testing”

Requirements

  • Python 3
  • Docker

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. Write the failing test first for the boundary or regression ([BE-TEST-05]).
  2. Patch one seam high enough to keep the test readable ([BE-TEST-04]).
  3. Assert structured outcomes: metadata, route result, blocker text, emitted command ([BE-TEST-03]).
  4. Use async tests for async code; avoid spinning real event loops manually.
  5. Cover negative paths for malformed packets, stale runtime state, and missing env.

What it can do on your machine

Read from SKILL.md and the folder at commit 1fb0537. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Python Testing loads about 851 tokens when it runs, and up to ~970 if it reads all its reference files. Until then it costs about 54 tokens; SKILL.md has 354 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~54
When it runs · the whole SKILL.md, loaded when a task matches
~851
With references · SKILL.md plus every file in references/, read only if the agent opens them
~970

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from HoangNguyen0403/agent-skills-standard at commit 1fb0537, republished under its MIT licence (© HoangNguyen0403). 354 words, ~851 tokens.

Download SKILL.mdSave it as .claude/skills/python-testing/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
python-testing
description
Test Python services with pytest, async coverage, monkeypatch, and boundary-focused fakes. Use when writing Python tests, fixtures, async tests, regression tests, or dependency-isolated verification.

Python Testing

Priority: P0 (CRITICAL)

Core Rule Anchors

  • [BE-TEST-01] Parametrized Tests for Equivalent Inputs: Prefer pytest.mark.parametrize for equivalent inputs and boundary permutations. Distinct scenarios may stay separate.
  • [BE-TEST-02] Ban on Brittle SQL String Matching: Test pure domain calculations directly or use fakes/testcontainers; do not regex-match SQL strings in mocks.
  • [BE-TEST-03] Ban on Shallow Assertions: Never assert only assert result without inspecting domain attributes and invariants.
  • [BE-TEST-04] Ban on Pass-Through Seam Mocks: Repositories and adapters must test contract compliance and error mapping; ban 1:1 pass-through mock echoing.
  • [BE-TEST-05] Bug-First Regression Lock: Every PR fixing a bug ticket or with title fix(...) must introduce a failing test reproducing the defect before fixing it.

Rules

  • Use pytest and pytest-asyncio for async boundaries.
  • Add regression tests around contract parsing, workflow routing, and verifier outcomes ([BE-TEST-05]).
  • Prefer pytest.mark.parametrize for equivalent inputs; distinct scenarios may stay separate ([BE-TEST-01]).
  • Prefer fakes or monkeypatch at external seams: DB, RPC, Telegram, subprocess, Docker ([BE-TEST-02], [BE-TEST-04]).
  • Verify behavior and domain invariants, not shallow truthiness or implementation trivia ([BE-TEST-03]).
  • Coverage is diagnostic and project-configured; verify risk-weighted critical paths rather than padding code for an arbitrary percentage.
Show full SKILL.md (169 more words)Show less

Recipe

  1. Write the failing test first for the boundary or regression ([BE-TEST-05]).
  2. Patch one seam high enough to keep the test readable ([BE-TEST-04]).
  3. Assert structured outcomes: metadata, route result, blocker text, emitted command ([BE-TEST-03]).
  4. Use async tests for async code; avoid spinning real event loops manually.
  5. Cover negative paths for malformed packets, stale runtime state, and missing env.

Anti-Patterns

  • [BE-TEST-01] Stylistic parametrize rewrites: Do not demand parameterized rewrites of passing tests without a behavioral gap.
  • [BE-TEST-02] SQL regex matching: Do not regex-match SQL strings in mocks.
  • [BE-TEST-03] Shallow assertions: Never assert only assert result; always verify domain attributes and invariants.
  • [BE-TEST-04] Pass-through seam mocks: Ban 1:1 mock echoing without contract assertions.
  • [BE-TEST-05] Bug fix without reproduction test: Ban bug fixes without a reproduction test.
  • No live network or DB in unit tests: Use fakes or testcontainers.
  • No broad monkeypatch spray: Patch the boundary, not every helper under it.
  • No smoke-only proof for shared runtime changes: Add focused assertions too.

References

© HoangNguyen0403, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files (references) in skills/python/python-testing of HoangNguyen0403/agent-skills-standard.

  • SKILL.md
  • evals/evals.json
  • references/pytest-patterns.md

Open the folder on GitHubat commit 1fb0537

Compare with similar skills

Python Testing next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Python Testing compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Python Testing this skillHoangNguyen0403/agent-skills-standard570—~851Automated safety check: PassMIT
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Hermetic Python Unit TestsdimensionalOS/dimos4.6k—~1.4kAutomated safety check: PassCustom licence
ONNX Runtime Test Runnermicrosoft/onnxruntime22k—~1.8kAutomated safety check: PassMIT
Simple Modern Uvjlevy/simple-modern-uv301—~1.9kAutomated safety check: PassMIT
Test Coverage Reviewareed1192/finance-news-aggregator149—~2.6kAutomated safety check: PassMIT

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Works with

Categories

Questions about Python Testing

What does Python Testing do?

Test Python services with pytest, async coverage, monkeypatch, and boundary-focused fakes. Python Testing is an agent skill from HoangNguyen0403/agent-skills-standard. Test Python services with pytest, async coverage, monkeypatch, and boundary-focused fakes.

When should I use Python Testing?

Python Testing fits situations like: writing Python tests; regression tests; dependency-isolated verification.

How do I install Python Testing in Claude Code?

Run `npx skills add HoangNguyen0403/agent-skills-standard --skill python-testing -a claude-code`. Or copy the skill folder (skills/python/python-testing in HoangNguyen0403/agent-skills-standard) into .claude/skills/python-testing in your project. Claude Code loads it when a task matches its description.

How do I install Python Testing in Codex?

Run `npx skills add HoangNguyen0403/agent-skills-standard --skill python-testing -a codex`. Or copy the skill folder (skills/python/python-testing in HoangNguyen0403/agent-skills-standard) into .agents/skills/python-testing in your project. Codex loads it when a task matches its description.

Can I use Python Testing in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add HoangNguyen0403/agent-skills-standard --skill python-testing -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/python-testing, .gemini/skills/python-testing, .github/skills/python-testing and .opencode/skills/python-testing in your project.

What does Python Testing need to run?

SKILL.md names no scripts, command-line tools or credentials: Python Testing is instructions for the agent only. Our summary lists: Python 3; Docker.

Does Python Testing access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Python Testing safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Python Testing use?

Python Testing is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Python Testing use?

About 851 tokens (SKILL.md is roughly 3.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 119 tokens, read only when the agent opens those files.

What are the alternatives to Python Testing?

Skills that share tags, products or a category with Python Testing: Adk Verify Snippets (google/adk-python, 22k stars), Hermetic Python Unit Tests (dimensionalOS/dimos, 4.6k stars), ONNX Runtime Test Runner (microsoft/onnxruntime, 22k stars) and Simple Modern Uv (jlevy/simple-modern-uv, 301 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Python Testing?

HoangNguyen0403 (a GitHub user) maintains it in HoangNguyen0403/agent-skills-standard, which has 570 GitHub stars. The repository holds 218 skills in this directory. The repository was last updated on October 6, 2026.

Source: HoangNguyen0403/agent-skills-standard on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.