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 EliasOulkadi/shokunin --skill ci-cdgit clone --depth 1 https://github.com/EliasOulkadi/shokuninWrote 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/eliasoulkadi/shokunin/ci-cd)<a href="https://agentmods.dev/skills/eliasoulkadi/shokunin/ci-cd"><img src="https://agentmods.dev/badge/skills/eliasoulkadi/shokunin/ci-cd/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/eliasoulkadi/shokunin/ci-cd"><img src="https://agentmods.dev/badge/skills/eliasoulkadi/shokunin/ci-cd.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 | $0.00132 | $0.03360 |
| Opus 5 | $0.00066 | $0.01680 |
| Sonnet 5 | $0.00026 | $0.00672 |
| Haiku 4.5 | $0.00013 | $0.00336 |
Grade C, and why
ci-cd scanned grade C with 2 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
| `No space left on device` | Build artifacts filling runner disk | Add cleanup step: `rm -rf /tmp/*` or use `actions/upload-artifact` with retention; reduce Docker image size | Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
STATUS=$(curl -so /dev/null -w '%{http_code}' https://app.example.com/health) How it starts
The opening of the file, as written. The whole thing — 322 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CI/CD Architect
Design fast, reliable, and secure CI/CD pipelines across GitHub Actions, GitLab CI, and CircleCI. Follows Google's DevOps capabilities and DORA metrics.
Decision Framework
Before building a CI/CD pipeline, answer:
- Where is the code hosted? → If GitHub, start with GitHub Actions. If GitLab, use GitLab CI. On-prem? Consider self-hosted.
- What's the deployment target? → Cloud (use OIDC), on-prem (use self-hosted runner), multi-cloud (use environment-specific jobs)
- Is the team size 1-3? → Simple single-workflow. 10+? → Separate build, test, deploy workflows with artifact passing.
- Do you need matrix builds (multiple OS/versions)? → Yes for libraries, no for single-platform apps.
- Is the deploy target production? → Require manual approval gates. Non-prod: automatic on merge.
Workflow
Step 1: Choose platform
| Platform | Best for | Config location |
|---|---|---|
| GitHub Actions | OSS, GitHub ecosystem | .github/workflows/*.yml |
| GitLab CI | Self-hosted, monorepos | .gitlab-ci.yml |
| CircleCI | Performance, Docker | .circleci/config.yml |
Decision: If the project is on GitHub.com, use GitHub Actions. If self-hosted GitLab, use GitLab CI. If maximum performance needed, use CircleCI.
Step 2: Generate pipeline
Use the scaffold script with your platform and stack:
scripts/generate-pipeline.sh --platform github --language node --e2e --docker
scripts/generate-pipeline.sh --platform gitlab --language python --docker
scripts/generate-pipeline.sh --platform circle --language go --e2e
This generates a production-ready pipeline with:
- Lint → typecheck → test (sharded) → build → docker → deploy
- Caching (npm/pip/go, Docker layers)
- OIDC auth (no static secrets)
- Environment gates (staging → production)
Step 3: Configure caching
| Cache type | GitHub Actions | GitLab CI | CircleCI |
|---|---|---|---|
| npm/pip/go | actions/cache with lockfile hash |
cache:key: with lockfile hash |
save_cache / restore_cache |
| Docker layers | docker/build-push-action GHA cache |
Docker layer caching on self-hosted | Remote Docker engine cache |
| Playwright browsers | npx playwright install chromium |
before_script cache |
Custom Docker image with browsers |
| Build artifacts | upload-artifact / download-artifact |
artifacts: section |
persist_to_workspace |
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.
- 10d ago First seen · 322 lines · 132 tokens per session scan C 500bf7d417e0
ci-cd is a skill published in the GitHub repository EliasOulkadi/shokunin (113 stars, last pushed 1mo ago), licensed MIT. It adds 132 tokens to every session and 3,360 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it C with 2 findings (recursive force delete, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
gitlab-integration
GitLab operations via glab CLI. Use when working with GitLab merge requests, issues, CI/CD pipelines, or repository operations. Triggers include creating/viewing/merging MRs, checking pipeline status, managing issues, and any GitLab-specific tasks.
autonomous-loops
Patterns and architectures for autonomous Claude Code loops — from simple sequential pipelines to RFC-driven multi-agent DAG systems.
deployment-patterns
Deployment workflows, CI/CD pipeline patterns, Docker containerization, health checks, rollback strategies, and production readiness checklists for web applications. Use when setting up deployment infrastructure or planning releases.
playwright-testing
E2E testing with Playwright - Page Objects, cross-browser, CI/CD.
memstack-deployment-ci-cd-pipeline
Use this skill when the user says 'CI/CD', 'GitHub Actions', 'pipeline', 'continuous integration', 'continuous deployment', 'ci-cd-pipeline', 'automate deploys', or needs to set up automated build, test, and deployment pipelines. Do NOT use for one-time manual deployments.
repo-scaffold
Scaffold or standardize a production-ready repository structure with specs, source layout, tests, CI, agent context, config examples, release notes, and operational docs. Use when starting a new repo, turning a prototype into a maintainable project, adding missing repository foundations, or creating a repo skeleton…