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 mikeparcewski/wicked-garden --skill unit-test-qualitygit clone --depth 1 https://github.com/mikeparcewski/wicked-gardenWrote 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/mikeparcewski/wicked-garden/unit-test-quality)<a href="https://agentmods.dev/skills/mikeparcewski/wicked-garden/unit-test-quality"><img src="https://agentmods.dev/badge/skills/mikeparcewski/wicked-garden/unit-test-quality/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/mikeparcewski/wicked-garden/unit-test-quality"><img src="https://agentmods.dev/badge/skills/mikeparcewski/wicked-garden/unit-test-quality.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00140 | $0.02323 |
| Opus 5 | $0.00070 | $0.01162 |
| Sonnet 5 | $0.00028 | $0.00465 |
| Haiku 4.5 | $0.00014 | $0.00232 |
Grade A, and why
wicked-garden-engineering-unit-test-quality scanned grade A with 1 finding 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 10d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
result = service.fetch(1); How it starts
The opening of the file, as written. The whole thing — 195 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Unit Test Quality
A test you cannot break by changing the system under test (SUT) is not a test — it is dead weight. This skill exists because suites grow faster than they shrink, and "100% coverage" is no defense against a suite that asserts the wrong things.
Two complementary filters
No single mechanical filter catches every useless test — each anti-pattern below has its own diagnostic. But two thought experiments catch the most common cases and are language-neutral. Apply them in order; if either says "cut," you are looking at a test that does not earn its keep.
Filter A — execution check
If I replace the body of the SUT with a force-fail (
throw/raise/panic/ equivalent), does the test still pass?
- Still passes → the test never exercised the SUT at all. Cut it (it is pure coverage theater, see #2 assertion-free, #4 framework retest).
- Now fails → the test at least invokes the SUT. Move to Filter B.
Filter B — behavior check
If I replace the body of the SUT with a no-op stub returning sensible defaults (zero, null/None, empty collection, default-constructed value), does the test still pass?
- Still passes → the test asserts nothing the SUT actually computes; the assertion would hold against an empty stub. Cut it (typically #5 constant verification or #4 framework retest).
- Now fails → the test depends on SUT-derived behavior. Likely worth keeping, but still apply the per-pattern rules below.
The filters are first-cut diagnostics — both can pass on #1 tautological (assertion mirrors mock input), #3 implementation mirror (assertion locks structure, not behavior), #6 sleep-coupled (timing flake is orthogonal), and #7 exception-swallowing (assertion-count guards are required regardless). Use the per-pattern decision rules below for those.
The seven useless-test anti-patterns
1. Tautological — asserts what the mock was told to return
when(repo.find(1)).thenReturn(user);
result = service.fetch(1);
assert(result == user); // Tests that the mock was wired correctly. The
// production fetch() could be `return repo.find(id)`
// OR `return repo.find(id).asJson().broken()` — this
// test cannot distinguish.
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.
- 10d ago First seen · 195 lines · 140 tokens per session scan A b2faa2e266e2
wicked-garden-engineering-unit-test-quality is a skill published in the GitHub repository mikeparcewski/wicked-garden (9 stars, last pushed today), licensed MIT. It adds 140 tokens to every session and 2,323 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
migrate-xunit-to-xunit-v3
Migrate .NET test projects from xUnit.net v2 to xunit.v3 and fix v3 breaks. Use for package/CPM conversion, OutputType=Exe, preserving the VSTest or MTP runner (including projects currently using YTest.MTP.XUnit2), incompatible TFMs, async void tests, string-to-Type attributes, custom Fact/Theory/BeforeAfterTest…
go-testing
Trigger: Go tests, go test coverage, Bubbletea teatest, golden files. Apply focused Go testing patterns.
nw-fp-clojure
Clojure language-specific patterns, data-first modeling, REPL-driven development, and spec.
mobiai-ios-testing
Use when writing or running tests in an iOS project — unit tests, UI tests, snapshot tests, choosing the right framework.
restore-internals-seams-in-finally-blocks-after-each-test
When delegating a task affected by this skill, include.
testing-llm
LLM and AI testing patterns — mock responses, evaluation with DeepEval/RAGAS, structured output validation, and agentic test patterns (generator, healer, planner). Use when testing AI features, validating LLM outputs, or building evaluation pipelines.