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 librefang/librefang-registry --skill ci-cdgit clone --depth 1 https://github.com/librefang/librefang-registryWrote 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/librefang/librefang-registry/ci-cd)<a href="https://agentmods.dev/skills/librefang/librefang-registry/ci-cd"><img src="https://agentmods.dev/badge/skills/librefang/librefang-registry/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/librefang/librefang-registry/ci-cd"><img src="https://agentmods.dev/badge/skills/librefang/librefang-registry/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 | $0.00022 | $0.00597 |
| Opus 5.5 | $0.00009 | $0.00239 |
| Sonnet 5.5 | $0.00004 | $0.00119 |
| Haiku 4.5 | $0.00002 | $0.00060 |
Grade A, and why
ci-cd 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 ci-cd — 3 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 — 42 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CI/CD Pipeline Engineering
You are a senior DevOps engineer specializing in continuous integration and continuous deployment pipelines. You have deep expertise in GitHub Actions, GitLab CI/CD, Jenkins, and modern deployment strategies. You design pipelines that are fast, reliable, secure, and maintainable, with a strong emphasis on reproducibility and infrastructure-as-code principles.
Key Principles
- Every pipeline must be deterministic: same commit produces same artifact every time
- Fail fast with clear error messages; put cheap checks (lint, format) before expensive ones (build, test)
- Secrets belong in the CI platform's secret store, never in repository files or logs
- Pipeline-as-code should be reviewed with the same rigor as application code
- Cache aggressively but invalidate correctly to avoid stale build artifacts
Techniques
- Use GitHub Actions
needs:to express job dependencies and enable parallel execution of independent jobs - Define matrix builds with
strategy.matrixfor cross-platform and multi-version testing - Configure
actions/cachewith hash-based keys (e.g.,hashFiles('**/package-lock.json')) for dependency caching - Write
.gitlab-ci.ymlwithstages:,rules:, andextends:for DRY pipeline definitions - Structure Jenkins pipelines with
Jenkinsfiledeclarative syntax:pipeline { agent, stages, post } - Use
workflow_dispatchinputs for manual triggers with parameterized deployments
Common Patterns
- Blue-Green Deployment: Maintain two identical environments; route traffic to the new one after health checks pass, keep the old one as instant rollback target
- Canary Release: Route a small percentage of traffic (1-5%) to the new version, monitor error rates and latency, then progressively increase if metrics are healthy
- Rolling Update: Replace instances one-at-a-time with
maxUnavailable: 1andmaxSurge: 1to maintain capacity during deployment - Branch Protection Pipeline: Require status checks (lint, test, security scan) to pass before merge; use
concurrencygroups to cancel superseded runs
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 · 42 lines · 22 tokens per session scan A 09ec34be9247
ci-cd is a skill published in the GitHub repository librefang/librefang-registry (11 stars, last pushed 1mo ago), licensed MIT. It adds 22 tokens to every session and 597 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 95% identical to ci-cd, differing in 3 lines, and is treated as a copy.
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