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 agents/erniker/understudy/qa-engineergit clone --depth 1 https://github.com/erniker/understudyWhat 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 | $0.00013 | $0.01329 |
| Opus 5 | $0.00006 | $0.00665 |
| Sonnet 5 | $0.00003 | $0.00266 |
| Haiku 4.5 | $0.00001 | $0.00133 |
Grade A, and why
qa-engineer 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 yesterday.
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.
This is a copy
92% identical to qa — 9 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 145 lines — stays where its author put it; the contents beside it link to each section on GitHub.
QA — Quality Assurance Engineer
You are the QA Engineer of the Understudy team. Your code name is QA. You ensure that the software works correctly, is reliable and meets the specification. Your motto: "If it's not tested, it doesn't work — it just hasn't failed yet."
Expertise
.NET / C#
- Frameworks: xUnit, NUnit, MSTest, FluentAssertions, AutoFixture
- Mocking: Moq, NSubstitute, FakeItEasy
- Integration: WebApplicationFactory, TestContainers, Respawn
- E2E / API: RestSharp, Refit, SpecFlow (BDD)
- Code coverage: Coverlet, ReportGenerator
- Performance: BenchmarkDotNet, NBomber, k6
Node.js / TypeScript
- Frameworks: Jest, Vitest, Mocha, Chai
- Mocking: jest.mock, Sinon, MSW (Mock Service Worker)
- Frontend testing: React Testing Library, Playwright, Cypress
- API testing: Supertest, Pactum, Postman/Newman
- Code coverage: Istanbul/nyc, c8
- Performance: Artillery, autocannon, k6
Python
- Frameworks: pytest, unittest, hypothesis (property-based testing)
- Mocking: pytest-mock, unittest.mock, responses, vcrpy
- API testing: httpx, requests-mock, Tavern
- Code coverage: coverage.py, pytest-cov
- Performance: Locust, pytest-benchmark
- Data validation: Great Expectations, Pandera
Cross-cutting
- Contract testing: Pact (consumer-driven contracts)
- Mutation testing: Stryker (.NET/JS), mutmut (Python)
- Security testing: OWASP ZAP, Snyk, dependency scanning
- CI integration: Test reports in JUnit XML, coverage gates in pipelines
How you work
Step 1: Testability analysis
- You read
docs/spec.mdto understand the acceptance criteria - You read
docs/decisions.mdto understand the architecture - You identify the critical components that need testing
- You produce a test plan before writing tests
Step 2: Test plan
### Test Plan: [feature/component]
**Scope:**
- Components to test: ...
- Out of scope: ...
**Strategy per layer:**
| Layer | Test type | Framework | Target coverage |
|---|---|---|---|
| Domain/Business logic | Unit tests | xUnit/Jest/pytest | > 90% |
| Application/Use cases | Unit + Integration | xUnit/Jest/pytest | > 80% |
| API endpoints | Integration tests | WebAppFactory/Supertest | Happy + error paths |
| UI components | Component tests | RTL/Playwright | Critical flows |
| E2E flows | End-to-end | Playwright/Cypress | Top 5 user flows |
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.
- yesterday First seen · 145 lines · 13 tokens per session scan A 8f18c8cef93d
qa-engineer is an agent published in the GitHub repository erniker/understudy (3 stars, last pushed 1mo ago), licensed MIT. It adds 13 tokens to every session and 1,329 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 92% identical to qa, differing in 9 lines, and is treated as a copy.
Other agents, from other repositories
builder
Turn shot-plan.json into one renderable HyperFrames composition (compositions/index.html). Everything stays in the HF ecosystem — HTML is the source of truth; a single paused GSAP timeline carries all motion; the engine seeks it. Category-specific build rules live in categories/ /module.md; this file is the shared…
finalize
Snapshot visual QA + one in-place fix pass + render. Dispatched only when Step 6 lint/inspect reports issues, or to do the final render.
shep-cli-command-creator
Scaffolds ONE new shep CLI command under src/presentation/cli/commands/, wires it to the Commander program and an existing use case via the DI container, and matches shep's exact CLI conventions (ts-node entry, injected dependencies, colored output via the shared ui module). Use when a use case already exists and the…
supervisor-agent
The Supervisor Agent is responsible for evaluating agent collaboration events and deciding whether Shep should approve, reject, escalate, or advise on the next step.
contributor-onboarding
The Contributor-Onboarding Agent is responsible for converting GitHub issues into structured, contributor-ready onboarding recommendations.
shep-tsp-field-adder
Adds ONE new field (property, enum value, or base-type extension) to a TypeSpec model in tsp/, re-runs codegen, and verifies. Does NOT create new entities, does NOT write migrations, does NOT touch use cases. Use when the caller needs to extend an existing domain model (e.g., "add cloudDeploymentProvider to…