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 gracefullight/docusaurus-plugins --skill oma-qagit clone --depth 1 https://github.com/gracefullight/docusaurus-pluginsWrote 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/gracefullight/docusaurus-plugins/oma-qa)<a href="https://agentmods.dev/skills/gracefullight/docusaurus-plugins/oma-qa"><img src="https://agentmods.dev/badge/skills/gracefullight/docusaurus-plugins/oma-qa/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/gracefullight/docusaurus-plugins/oma-qa"><img src="https://agentmods.dev/badge/skills/gracefullight/docusaurus-plugins/oma-qa.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 | $0.00058 | $0.01460 |
| Opus 5.5 | $0.00023 | $0.00584 |
| Sonnet 5.5 | $0.00012 | $0.00292 |
| Haiku 4.5 | $0.00006 | $0.00146 |
Grade A, and why
oma-qa 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 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.
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
95% identical to oma-qa — 25 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 — 146 lines — stays where its author put it; the contents beside it link to each section on GitHub.
QA Agent - Quality Assurance Specialist
Scheduling
Goal
Review and verify software quality with priority on security, performance, accessibility, correctness, test coverage, and standards-aligned quality evidence.
Intent signature
- User asks for review, QA, security audit, OWASP, performance, accessibility, coverage, lint, testing, or ISO/IEC quality recommendations.
- User needs findings with evidence, severity, file references, and concrete remediation.
When to use
- Final review before deployment
- Security audits (OWASP Top 10)
- Performance analysis
- Accessibility compliance (WCAG 2.2 AA)
- Test coverage analysis
When NOT to use
- Initial implementation -> let specialists build first
- Writing new features -> use domain agents
Expected inputs
- Diff, codebase area, PR, feature branch, build output, test results, or quality concern
- Applicable standards such as OWASP, WCAG, ISO/IEC 25010, or ISO/IEC 29119
- Verification commands and target environment when available
Expected outputs
- Ordered findings with severity, evidence, file/line references, and fixes
- Test, security, performance, accessibility, and quality recommendations
- Verification summary and residual risks
Dependencies
resources/execution-protocol.md, examples, ISO guide, checklist, and self-check- Automated tools such as
npm audit,bandit,lighthouse, linters, tests, and coverage tools when applicable
Control-flow features
- Branches by review type, available diff, quality dimension, and tool availability
- Reads code and reports; may run tools; generally should not implement broad feature work
- Findings must be reproducible and prioritized
Structural Flow
Entry
- Identify review scope and quality dimensions.
- Collect diff, files, commands, and standards context.
- Choose automated checks before manual review where practical.
Scenes
- PREPARE: Define scope, severity rubric, and evidence requirements.
- ACQUIRE: Read diff/code and run relevant automated tools.
- REASON: Analyze security, performance, accessibility, correctness, and test coverage.
- VERIFY: Reproduce findings and reject false positives.
- FINALIZE: Report findings, remediation, test gaps, and residual risk.
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 · 146 lines · 58 tokens per session scan A 739deef2e5fe
oma-qa is a skill published in the GitHub repository gracefullight/docusaurus-plugins (23 stars, last pushed 27d ago), licensed MIT. It adds 58 tokens to every session and 1,460 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 95% identical to oma-qa, differing in 25 lines, and is treated as a copy.
Other skills, from other repositories
engram-testing-coverage
TDD and coverage standards for Engram. Trigger: When implementing behavior changes in any package.
conductor-implement
Execute tasks from a track's implementation plan following TDD workflow.
principle-test-behavior-not-implementation
Apply when you write, change, or keep a test. Assert what the code's users can observe, so that the test fails when that behavior breaks and keeps passing when only the internals change.
iterative-development
TDD iteration loops using Claude Code Stop hooks - runs tests after each response, feeds failures back automatically.
tdd
This skill should be used when the user wants to implement features or fix bugs using test-driven development. Enforces the RED-GREEN-REFACTOR cycle with vertical slicing, context isolation between test writing and implementation, human checkpoints, and auto-test feedback loops. Uses multi-agent orchestration with the…
python
Python development with ruff, mypy, pytest - TDD and type safety.