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 Mathews-Tom/armory --skill test-harnessgit clone --depth 1 https://github.com/Mathews-Tom/armoryWrote 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/mathews-tom/armory/test-harness)<a href="https://agentmods.dev/skills/mathews-tom/armory/test-harness"><img src="https://agentmods.dev/badge/skills/mathews-tom/armory/test-harness/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/mathews-tom/armory/test-harness"><img src="https://agentmods.dev/badge/skills/mathews-tom/armory/test-harness.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Prompt Injection · line 216 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
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 | $0.00065 | $0.02799 |
| Opus 5.5 | $0.00026 | $0.01120 |
| Sonnet 5.5 | $0.00013 | $0.00560 |
| Haiku 4.5 | $0.00006 | $0.00280 |
Grade A, and why
test-harness 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 1mo 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.
not at the definition site. `@patch('mymodule.requests.get')`, not How it starts
The opening of the file, as written. The whole thing — 263 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Test Harness
Systematic test suite generation that transforms source code into comprehensive, runnable pytest files. Analyzes function signatures, dependency graphs, and complexity hotspots to produce tests covering happy paths, boundary conditions, error states, and async flows — with properly scoped fixtures and focused mocks.
Reference Files
| File | Contents | Load When |
|---|---|---|
references/pytest-patterns.md |
Fixture scopes, parametrize, marks, conftest layout, built-in fixtures | Always |
references/mock-strategies.md |
Mock decision tree, patch boundaries, assertions, anti-patterns | Target has external dependencies |
references/async-testing.md |
pytest-asyncio modes, event loop fixtures, async mocking | Target contains async code |
references/fixture-design.md |
Factory fixtures, yield teardown, scope selection, composition | Test requires non-trivial setup |
references/coverage-targets.md |
Threshold table, branch vs line, pytest-cov config, exclusion patterns | Coverage assessment requested |
Prerequisites
- pytest >= 7.0
- Python >= 3.10
- pytest-asyncio — required only when generating async tests
- pytest-mock — optional, provides
mockerfixture as alternative tounittest.mock
Workflow
Phase 1: Reconnaissance
Before writing a single test, build a model of the target code:
- Identify scope — What functions, classes, or modules need tests? If unspecified,
check for recent modifications:
git diff --name-only HEAD~5 - Read function signatures — Parameters, types, return types, defaults. Every parameter is a test dimension.
- Map dependencies — Which calls go to external systems (DB, API, filesystem, clock)? These are mock candidates.
- Detect complexity hotspots — Functions with high branch counts, deep nesting, or multiple return paths need more test cases.
- Check existing tests — If tests already exist, understand what they cover. Do not duplicate; extend.
- Read project conventions — Check CLAUDE.md, conftest.py, pytest.ini/pyproject.toml for fixtures, markers, and test organization patterns already in use.
What ships with it
7 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.
- 1mo ago First seen · 263 lines · 65 tokens per session scan A b5b4ef5496b9
test-harness is a skill published in the GitHub repository Mathews-Tom/armory (334 stars, last pushed yesterday), licensed MIT. It adds 65 tokens to every session and 2,799 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-09-05.
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