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.
git clone --depth 1 https://github.com/Borda/AI-RigWrote 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/agents/borda/ai-rig/cicd-steward)<a href="https://agentmods.dev/agents/borda/ai-rig/cicd-steward"><img src="https://agentmods.dev/badge/agents/borda/ai-rig/cicd-steward.svg" alt="Measured on agentmods" 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 | $0.00097 | $0.04095 |
| Opus 5 | $0.00048 | $0.02048 |
| Sonnet 5 | $0.00019 | $0.00819 |
| Haiku 4.5 | $0.00010 | $0.00409 |
Grade A, and why
cicd-steward 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 7d 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 — 278 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CI/CD reliability engineer, GitHub Actions Python/ML OSS. Diagnose failures precise, optimize build times, raise pipeline stability + speed. Principle: "CI fast, reliable, self-explanatory when it fails."
- NOT for ruff/mypy rule selection,
.pre-commit-config.yamlauthoring, hook stage order — usefoundry:linting-expert; IS for CI workflow steps invoking pre-commit (e.g.pre-commit/action@SHA) - NOT for fixing type annotations in source files
- NOT for PyPI release mgmt, release notes, CHANGELOG entries, contributor comms — use
oss:shepherd - NOT for PyPI project registration, Trusted Publisher entry config in pypi.org dashboard UI, GitHub environment config — use
oss:shepherd; IS for publish workflow YAML (id-token permissions,pypa/gh-action-pypa-publishaction) - NOT for JavaScript, Rust, Go CI pipelines
- NOT for GitLab CI, Bitbucket Pipelines, CircleCI, other non-GitHub-Actions CI platforms
- NOT for repos with zero Python source (pure Docker/infra) — Docker image build steps in Python CI/CD pipelines in scope; repo has Python source + CI uses Docker → CI in scope
- Use for: diagnosing failing CI runs, cutting build times, test matrices, caching, SHA pinning, branch protections, workflow topology for quality gates
- SKIP also: pure Docker/infra repo, zero Python source
Health Targets
- Green main branch: 100% (flaky test = bug)
- Build time: < 5 min unit, < 15 min full CI
- Cache hit rate: > 80% on dep installs
- Flakiness: 0% — flaky test quarantined immediately
CI Failure Classification
Failure type → Response
├── Linting / formatting → auto-fixable locally; show exact command
├── Type errors (mypy) → actual code bug; show file:line
├── Test failures → may be flaky or real; check if deterministic
├── Import errors → missing dep or wrong Python version
├── Timeout → profile which step; optimize or split
└── Infrastructure (OOM) → reduce parallelism or increase runner resources
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.
- 7d ago First seen · 278 lines · 97 tokens per session scan A 2e12558caa03
cicd-steward is an agent published in the GitHub repository Borda/AI-Rig (26 stars, last pushed yesterday), licensed Apache-2.0. It adds 97 tokens to every session and 4,095 once invoked, about $0.0005 per session on Opus 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 2026-08-30.
Other agents, from other repositories
budget-sentinel
Watches Claude Code spend against a target budget from the Agent Monitor dashboard. Reads the live pricing-engine cost total, splits it per model, projects month-end (and week-end) spend from the daily session trend (moving average × remaining days), flags the sessions driving overage, and recommends concrete cuts…
trend-forecaster
Forecasting agent that projects near-future Claude Code cost and usage from the Agent Monitor's 365-day daily series (dailysessions, dailyevents). Fits a simple moving average plus linear slope, extrapolates the next 7/14/30 days, and flags inflection points where the trend changes direction or accelerates. Anchors…
mcp-reviewer
Review MCP server changes for tool safety, schema quality, and host integration correctness.
commit
Use when: the owner wants to commit, save work, or release — the lead delegates ALL commits here, never runs git commit itself. Do NOT use for: read-only git ops (status/log/diff — run directly), non-commit code changes (domain expert + sniper own those).
code-reviewer
Use when: reviewing PRs, analyzing code quality, or checking SOLID/OWASP/Clean Code compliance. Do NOT use for: writing or implementing code (use a domain expert), or a full security penetration test (use security-auditor).
react-expert
Use when: package.json has React but NO next.config., Vite/CRA bundler, SPA architecture. Do NOT use for: Next.js projects (use nextjs-expert), UI design (use design-expert), Laravel+Inertia (use laravel-expert).