Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/yonatangross/orchestkit/testing-unitnpx skills add yonatangross/orchestkit --skill testing-unitgit clone --depth 1 https://github.com/yonatangross/orchestkitWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/yonatangross/orchestkit/testing-unit)<a href="https://agentmods.dev/skills/yonatangross/orchestkit/testing-unit"><img src="https://agentmods.dev/badge/skills/yonatangross/orchestkit/testing-unit.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00095 | $0.02442 |
| Opus 5 | $0.00048 | $0.01221 |
| Sonnet 5 | $0.00019 | $0.00488 |
| Haiku 4.5 | $0.00010 | $0.00244 |
Grade A, and why
testing-unit scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 273 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Unit Testing Patterns
Focused patterns for writing isolated, fast, maintainable unit tests. Covers test structure (AAA), parametrization, fixture management, HTTP mocking (MSW/VCR), and test data generation with factories.
Each category has individual rule files in rules/ loaded on-demand, plus reference material, checklists, and scaffolding scripts.
Core Principles (ALWAYS apply)
- AAA structure: Every test MUST follow Arrange-Act-Assert. Use
// Arrange,// Act,// Assertcomments for clarity. - Parametrize, don't duplicate: Use
test.each(TypeScript) or@pytest.mark.parametrize(Python) when testing multiple inputs. Never copy-paste the same test body with different values. - Fixture scoping matters: Use
scope="function"(default) for mutable data. Usescope="module"orscope="session"ONLY for expensive read-only resources (DB engines, ML models). Mutable data with shared scope causes flaky tests. - Speed target: Each unit test should run under 100ms. If it's slower, you're likely hitting I/O — mock it.
- Mock at the network level: Use MSW (TypeScript) or VCR.py (Python) to intercept HTTP at the network layer. Never mock
fetch/axios/requestsdirectly.
Quick Reference
| Category | Rules | Impact | When to Use |
|---|---|---|---|
| Unit Test Structure | 3 | CRITICAL | Writing any unit test |
| HTTP Mocking | 2 | HIGH | Mocking API calls in frontend/backend tests |
| Test Data Management | 3 | MEDIUM | Setting up test data, factories, fixtures |
Total: 8 rules across 3 categories, 4 references, 3 checklists, 1 example set, 3 scripts
Unit Test Structure
Core patterns for structuring isolated unit tests with clear phases and efficient execution.
| Rule | File | Key Pattern |
|---|---|---|
| AAA Pattern | rules/unit-aaa-pattern.md |
Arrange-Act-Assert with isolation |
| Fixture Scoping | rules/unit-fixture-scoping.md |
function/module/session scope selection |
| Parametrized Tests | rules/unit-parametrized.md |
test.each / @pytest.mark.parametrize |
What ships with it
21 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- checklists/msw-setup-checklist.md 3.0 KB
- checklists/test-data-checklist.md 749 B
- checklists/vcr-checklist.md 1.3 KB
- examples/handler-patterns.md 9.8 KB
- references/aaa-pattern.md 1.9 KB
- references/factory-patterns.md 2.2 KB
- references/msw-2x-api.md 5.9 KB
- references/stateful-testing.md 4.1 KB
- rules/_sections.md 1.2 KB
- rules/data-factories.md 1.9 KB
- rules/data-fixtures.md 1.8 KB
- rules/data-seeding-cleanup.md 1.7 KB
- rules/mocking-msw.md 2.4 KB
- rules/mocking-vcr.md 2.4 KB
- rules/unit-aaa-pattern.md 2.0 KB
- rules/unit-fixture-scoping.md 1.9 KB
- rules/unit-parametrized.md 2.3 KB
- scripts/create-msw-handler.md 1.6 KB
- scripts/create-test-case.md 1.9 KB
- scripts/create-test-fixture.md 1.5 KB
- test-cases.json 2.9 KB
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- today First seen · 273 lines · 95 tokens per session scan A 07dd65accf66
testing-unit is a skill published in the GitHub repository yonatangross/orchestkit (228 stars, last pushed yesterday), licensed MIT. It adds 95 tokens to every session and 2,442 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-05.
Other skills, from other repositories
vitest
Vitest unit testing — Vite-powered, Jest-compatible. Use when writing tests, mocking, configuring coverage, or working with test filtering and fixtures.
pytest
Advanced Python unit testing framework for customer support tech enablement, covering FastAPI, SQLAlchemy, PostgreSQL, async operations, mocking, fixtures, parametrization, coverage, and comprehensive testing strategies for backend support systems.
temporal-python-testing
Test Temporal workflows with pytest, time-skipping, and mocking strategies. Covers unit testing, integration testing, replay testing, and local development setup. Use when implementing Temporal workflow tests or debugging test failures.
adk-verify-snippets
Checks that every Python code block in a Markdown file actually compiles and runs, by extracting each block to a temporary file, executing it in an isolated subprocess, and writing a pass/fail report with per-snippet coverage. Use when the user asks to verify, test, or validate the code samples in a README, a guide…
adk-setup
Sets up a local ADK Python development environment in a git clone of the open-source adk-python repository: a uv virtual environment, all dependency extras, pre-commit hooks, and a first unit-test run. Runs only when explicitly requested, never on its own. Use when asked to set up, bootstrap, or repair a development…
Jest Mocking Patterns
Teaches the agent the right way to mock in Jest — jest.fn, mockImplementation, mockResolvedValue, jest.mock factories, spyOn with restore, and isolating modules like axios.