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 skills add jeremylongworth-source/AgentSkills --skill unit-test-generationgit clone --depth 1 https://github.com/jeremylongworth-source/AgentSkillsWrote 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/jeremylongworth-source/agentskills/unit-test-generation)<a href="https://agentmods.dev/skills/jeremylongworth-source/agentskills/unit-test-generation"><img src="https://agentmods.dev/badge/skills/jeremylongworth-source/agentskills/unit-test-generation/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/jeremylongworth-source/agentskills/unit-test-generation"><img src="https://agentmods.dev/badge/skills/jeremylongworth-source/agentskills/unit-test-generation.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00051 | $0.00293 |
| Opus 5 | $0.00026 | $0.00147 |
| Sonnet 5 | $0.00010 | $0.00059 |
| Haiku 4.5 | $0.00005 | $0.00029 |
Grade A, and why
unit-test-generation 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 8d ago.
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.
What it actually says
Unit Test Generation
Core Workflow
- Identify the unit under test, behavior changed, dependencies, inputs, outputs, and edge cases.
- Read existing tests and local test patterns before proposing new tests.
- Define test cases for normal behavior, boundaries, invalid inputs, errors, and regressions.
- Prefer deterministic tests with minimal mocking and clear assertions.
- Include fixture needs, setup/teardown, and test command.
- State what remains untested and whether integration or E2E coverage is needed.
Safety Rules
- Do not claim tests pass without command output.
- Do not add brittle tests that assert implementation details unless that is the contract.
- Do not use production data, real credentials, or live external services.
Deliverable Shape
For unit test work, provide:
- Unit and behavior under test
- Test case list
- Fixtures and mocks
- Edge and regression cases
- Test file or command
- Coverage gaps
- Validation notes
References
- Read
references/unit-test-generation-checklist.mdwhen planning or adding unit tests.
What ships with it
2 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.
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.
- 8d ago First seen · 44 lines · 51 tokens per session scan A ff81ca819ac5
unit-test-generation is a skill published in the GitHub repository jeremylongworth-source/AgentSkills (1 stars, last pushed 9d ago), licensed MIT. It adds 51 tokens to every session and 293 once invoked, about $0.0003 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 2026-09-03.
Other skills, from other repositories
nemo-automodel-model-onboarding
Guide for onboarding new model architectures into NeMo AutoModel, including architecture discovery, implementation patterns, registration, and validation.
nemo-automodel-recipe-development
Create and modify NeMo AutoModel training and evaluation recipes, including YAML structure, builders, and execution flow.
mcore-testing
Test system for Megatron-LM. Covers test layout, recipe YAML structure, adding and running unit and functional tests, golden values, marker filters, and CI parity.
i4h-catheter-navigation-e2e
End-to-end smoke for catheter navigation covering setup, digital twin, DRR, and unit tests. Use when asked to run the full catheter workflow smoke or demo the v0.7 pipeline.
test-harness
Generates pytest test suites with happy path, edge cases, error conditions, fixture scaffolding, mocks, async patterns. Triggers on: "generate tests", "write tests for", "test this function", "create test suite", "pytest for", "unit tests for", "mock strategy for".
nemo-mbridge-mlm-bridge-training
Run Megatron-LM (MLM) and Megatron Bridge training with mock or real data. Covers correlation testing, available recipes, and multi-GPU examples.