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 curiositech/some_claude_skills --skill github-actions-pipeline-buildergit clone --depth 1 https://github.com/curiositech/some_claude_skillsWrote 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/curiositech/some_claude_skills/github-actions-pipeline-builder)<a href="https://agentmods.dev/skills/curiositech/some_claude_skills/github-actions-pipeline-builder"><img src="https://agentmods.dev/badge/skills/curiositech/some_claude_skills/github-actions-pipeline-builder/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/curiositech/some_claude_skills/github-actions-pipeline-builder"><img src="https://agentmods.dev/badge/skills/curiositech/some_claude_skills/github-actions-pipeline-builder.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
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 →
- high Privilege Escalation · line 202 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
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 | $0.00079 | $0.02855 |
| Opus 5.5 | $0.00032 | $0.01142 |
| Sonnet 5.5 | $0.00016 | $0.00571 |
| Haiku 4.5 | $0.00008 | $0.00285 |
Grade A, and why
github-actions-pipeline-builder 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.
How it starts
The opening of the file, as written. The whole thing — 474 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GitHub Actions Pipeline Builder
Expert in building production-grade CI/CD pipelines with GitHub Actions that are fast, reliable, and secure.
When to Use
✅ Use for:
- Automated testing on every commit
- Deployment to staging/production
- Docker image building and publishing
- Release automation with versioning
- Security scanning and dependency audits
- Code quality checks (linting, type checking)
- Multi-environment workflows
❌ NOT for:
- Non-GitHub repositories (use Jenkins, CircleCI, etc.)
- Complex pipelines better suited for dedicated CI/CD tools
- Self-hosted runners (covered in advanced patterns)
Quick Decision Tree
Does your project need:
├── Testing on every PR? → GitHub Actions
├── Automated deployments? → GitHub Actions
├── Matrix builds (Node 16, 18, 20)? → GitHub Actions
├── Secrets management? → GitHub Actions secrets
├── Multi-cloud deployments? → GitHub Actions + OIDC
└── Sub-second builds? → Consider build caching
Technology Selection
GitHub Actions vs Alternatives
Why GitHub Actions in 2024:
- Native integration: No third-party setup
- Free for public repos: 2000 minutes/month for private
- Matrix builds: Test multiple versions in parallel
- Marketplace: 10,000+ pre-built actions
- OIDC support: Keyless cloud deployments
Timeline:
- 2019: GitHub Actions released
- 2020: Became standard for OSS projects
- 2022: OIDC support for secure cloud auth
- 2024: De facto CI/CD for GitHub repos
When to Use Alternatives
| Scenario | Use | Why |
|---|---|---|
| Self-hosted GitLab | GitLab CI | Native integration |
| Complex enterprise workflows | Jenkins | More flexible |
| Bitbucket repos | Bitbucket Pipelines | Native integration |
| Extremely large repos (>10GB) | BuildKite | Better for monorepos |
Common Anti-Patterns
Anti-Pattern 1: No Dependency Caching
Novice thinking: "Install dependencies fresh every time for consistency"
Problem: Wastes 2-5 minutes per build installing unchanged dependencies.
What ships with it
5 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 · 474 lines · 79 tokens per session scan A 94d9746220af
github-actions-pipeline-builder is a skill published in the GitHub repository curiositech/some_claude_skills (253 stars, last pushed 1mo ago), licensed MIT. It adds 79 tokens to every session and 2,855 once invoked, about $0.0003 per session on Opus 5.5. 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
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Comprehensive truth scoring, code quality verification, and automatic rollback system with 0.95 accuracy threshold for ensuring high-quality agent outputs and codebase reliability.
quality-scan
Run a scoped, read-only quality scan and report exact-candidate evidence, failures and frozen debt. Use for an ad-hoc gate sweep or release preparation; a static scan is not full release acceptance.
e2e-testing
Use when reviewing CI coverage, automated checks, or test strategy related to Implement end-to-end testing. Focus on whether the rule is continuously verified, not just documented.
mirrord-prev-env
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test-setup
Scaffold the test framework and CI — tests/ directory, engine test runner, GitHub Actions workflow. Once, before the first sprint.
ci
Configure Ginkgo for continuous integration — the recommended CLI flag set and the rationale for each flag (-r -p --randomize-all --randomize-suites --fail-on-pending --fail-on-empty --keep-going --cover --race --trace --json-report --timeout --poll-progress-after/-interval), invoking via go run to pin the CLI to…