Borrowing it
Nothing to install: this file belongs to AsiaOstrich/EngramGraph. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/AsiaOstrich/EngramGraph/main/.agents/skills/ci-cd-assistant/SKILL.mdgit clone --depth 1 https://github.com/AsiaOstrich/EngramGraphWrote 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/asiaostrich/engramgraph/ci-cd-assistant)<a href="https://agentmods.dev/skills/asiaostrich/engramgraph/ci-cd-assistant"><img src="https://agentmods.dev/badge/skills/asiaostrich/engramgraph/ci-cd-assistant/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/asiaostrich/engramgraph/ci-cd-assistant"><img src="https://agentmods.dev/badge/skills/asiaostrich/engramgraph/ci-cd-assistant.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 | $0.00068 | $0.02523 |
| Opus 5.5 | $0.00027 | $0.01009 |
| Sonnet 5.5 | $0.00014 | $0.00505 |
| Haiku 4.5 | $0.00007 | $0.00252 |
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 14d 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 — 156 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CI/CD Pipeline Assistant | CI/CD 管線助手
Language: English | 繁體中文
Guide CI/CD pipeline design following industry best practices and DORA metrics.
引導 CI/CD 管線設計，遵循業界最佳實踐與 DORA 指標。
Pipeline Stage Reference | 管線階段參考
BUILD ──► TEST ──► ANALYZE ──► DEPLOY ──► VERIFY
建置 測試 分析 部署 驗證
| Stage | Purpose | Key Activities | 關鍵活動 |
|---|---|---|---|
| Build | Compile & package | Dependency install, compilation, artifact creation | 安裝相依、編譯、產出成品 |
| Test | Quality verification | Unit, integration, E2E tests | 單元、整合、端對端測試 |
| Analyze | Code quality | Lint, security scan, coverage report | 程式碼檢查、安全掃描、覆蓋率 |
| Deploy | Release to environment | Staging → Production rollout | 預備環境 → 正式環境部署 |
| Verify | Post-deploy validation | Smoke tests, health checks, monitoring | 冒煙測試、健康檢查、監控 |
DORA Metrics Quick Reference | DORA 指標快速參考
| Metric | Elite | High | Medium | Low |
|---|---|---|---|---|
| Deployment Frequency 部署頻率 | On-demand (multiple/day) | Weekly–Monthly | Monthly–Biannual | > 6 months |
| Lead Time for Changes 變更前置時間 | < 1 hour | 1 day–1 week | 1–6 months | > 6 months |
| MTTR 平均恢復時間 | < 1 hour | < 1 day | 1 day–1 week | > 6 months |
| Change Failure Rate 變更失敗率 | 0–15% | 16–30% | 16–30% | > 30% |
Best Practices Checklist | 最佳實踐檢查清單
- Fail fast — Run fastest checks first (lint → unit → integration → E2E)
- Cache dependencies — Cache
node_modules,.m2, pip cache between runs - Parallel jobs — Split test suites across parallel runners
- Immutable artifacts — Build once, deploy the same artifact to all environments
- Environment parity — Keep staging identical to production
- Secrets management — Never hardcode secrets; use vault/environment variables
- Branch protection — Require CI pass before merge
- Rollback strategy — Automate rollback on deploy failure
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.
- 14d ago First seen · 156 lines · 68 tokens per session scan A c4414aec38f0
ci-cd is a skill published in the GitHub repository AsiaOstrich/EngramGraph (3 stars, last pushed today), licensed MIT. It adds 68 tokens to every session and 2,523 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 2026-10-16.
Other skills, from other repositories
kivgraph
Use Kivgraph's local MCP server to search symbols, read their source, and follow references, dependencies, cross-repository consumers and graph status in the indexed code graph.
mushroom
Live graph memory for agents — query and create entities, derive relationships by rule, explain why two things are associated, read the graph at a past commit, ask what a change would do, and answer as one role. Trigger on: memory, remember, recall, relationship, entity, association, why are X and Y related, as of…
omnigraph
Operate OmniGraph graphs and deployments. Use for .pg schemas, .gq queries, OmniGraph CLI commands, file:///s3:///az:// graph URIs, cluster.yaml, operator config, bearer-authenticated servers, graph-backed knowledge or memory, Blob values, embeddings, branches, commits, and change feeds. Apply especially before schema…
code-graph
This skill should be used when understanding code structure, finding dependencies between functions/classes, tracing call graphs, or exploring code relationships. Trigger phrases include 'code graph', 'call graph', 'who calls', 'what calls', 'find dependencies', 'code structure', 'inheritance', 'find paths'.
usage
Query LeanKG knowledge graph for code understanding. Use when exploring a codebase, finding functions, tracing dependencies, or calculating impact radius.
codestory-grounding
Use when discovering repository structure, tracing relationships, analyzing change impact, or validating CodeStory retrieval or an installed plugin through the CodeStory plugin MCP. Skip only for bounded inspection or editing of named files that does not require those operations.