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cicd-playbook

Write a CI/CD pipeline playbook for a service or team

Install / Use

npx skills add mohitagw15856/pm-claude-skills --skill cicd-playbook

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

83/100

Category

Automation

Supported Platforms

Universal

Tags

Our assessment of cicd-playbook

cicd-playbook scores 83/100 on our quality scale, 1846th of 2,790 Automation skills we index.

Its SKILL.md is 11 KB long, well organised into 29 sections with 2 code examples: a thorough specification that gives an agent plenty to work with.

With 1,396 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
29/30
Structure
18/20
Description
8/15
Adoption
13/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 7 days ago, so cicd-playbook is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

Safety scan

No issues found

Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands.

Automated pattern scan on 2026-10-01. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.

cicd-playbook compared with similar skills

All 4 of these similar skills score higher than cicd-playbook; compare them before choosing.

SkillScoreStarsUpdatedFormat
cicd-playbook (this skill)by mohitagw15856831.4k7d agoSKILL.md
Agent-Reachby Panniantong10087.2k15d agoCLAUDE.md
rufloby ruvnet10073.6ktodayCLAUDE.md
Scraplingby D4Vinci10084.9ktodayMCP Server
algorithmic-artby anthropics100177.9k8d agoSKILL.md

Frequently asked questions

How do I install cicd-playbook?
Run npx skills add mohitagw15856/pm-claude-skills --skill cicd-playbook. The install tabs above show the steps for each supported agent.
Which AI agents does cicd-playbook work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is cicd-playbook safe to use?
Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is cicd-playbook still maintained?
The repository was last updated 7 days ago, so cicd-playbook is actively maintained.

name: cicd-playbook description: "Write a CI/CD pipeline playbook for a service or team. Use when asked to document a CI/CD pipeline, write a deployment process, define release gates, document build and test stages, or create a deployment guide. Produces a structured playbook covering pipeline stages, environment definitions, deployment gates, rollback procedures, and on-call responsibilities."

CI/CD Playbook Skill

Produce a complete, actionable CI/CD playbook for a service or team — covering everything a new engineer needs to understand, contribute to, and operate the pipeline safely.

A good playbook is not a diagram. It is a document that answers: what runs, when, why, who owns it, and what to do when it breaks.

Required Inputs

Ask for these if not already provided:

  • Service name and brief description
  • Tech stack — language, framework, containerisation (Docker, etc.)
  • Source control — GitHub / GitLab / Bitbucket, branching strategy
  • CI platform — GitHub Actions / CircleCI / Jenkins / BuildKite / other
  • CD platform / deployment target — Kubernetes, ECS, Lambda, Heroku, VMs, etc.
  • Environments — e.g. dev, staging, production (and any canary / feature environments)
  • Deployment frequency — how often does the team ship?
  • Any existing gates — manual approvals, smoke tests, feature flags
  • On-call setup — who's responsible during deploys?

Output Format


CI/CD Playbook: [Service Name]

Service: [Name] | Team: [Team name] Last updated: [Date] | Owner: [Name / role] Pipeline platform: [CI tool] → [CD tool / platform]


Overview

[2–3 sentences describing what this service does and why the CI/CD pipeline is structured the way it is. Include the deployment target and how frequently the team ships.]

Deployment frequency: [Multiple times per day / Daily / Weekly / On-demand] Average pipeline duration: [X minutes] Rollback time (p95): [X minutes]


Pipeline Stages

[Branch push]
    │
    ▼
[1. Build & Lint] ──fail──▶ ❌ Block PR
    │
    ▼
[2. Unit Tests] ──fail──▶ ❌ Block PR
    │
    ▼
[3. Integration Tests] ──fail──▶ ❌ Block PR
    │
    ▼
[4. Security Scan] ──fail──▶ ⚠️ [Block / Warn — specify]
    │
    ▼
[5. Build Artefact / Container Image]
    │
    ▼
[6. Deploy to Staging] ──fail──▶ ❌ Block promotion
    │
    ▼
[7. Smoke Tests (Staging)]
    │
    ▼
[8. Manual Approval Gate] ──(if required)
    │
    ▼
[9. Deploy to Production] ──fail──▶ 🔁 Auto-rollback (if configured)
    │
    ▼
[10. Post-deploy checks]

Stage Definitions

Stage 1 — Build & Lint

What runs: [Build command] + [Linter — e.g. ESLint, golangci-lint, flake8] Trigger: Every commit to any branch Blocking: Yes — PR cannot be merged if this fails Typical duration: [X minutes] Owner if it fails: PR author

Common failure causes:

  • [e.g. Missing dependency — run npm install locally before pushing]
  • [e.g. Lint rule violation — run npm run lint --fix to auto-fix most issues]

Stage 2 — Unit Tests

What runs: [Test command — e.g. npm test, go test ./..., pytest] Coverage gate: [X]% minimum — pipeline fails below this threshold Trigger: Every commit Blocking: Yes Typical duration: [X minutes]

Coverage report: [Where to find it — e.g. uploaded to Codecov, available in CI artifacts]


Stage 3 — Integration Tests

What runs: [Test suite description — e.g. "API integration tests against a test database using Docker Compose"] Environment: [Ephemeral test environment / shared test DB / etc.] Trigger: Every commit to main and feature branches targeting main Blocking: Yes Typical duration: [X minutes]

If slow: [e.g. "Integration tests can be skipped locally with SKIP_INTEGRATION=true — never skip in CI"]


Stage 4 — Security Scan

Tools: [e.g. Snyk, Trivy, OWASP Dependency Check, Semgrep] What it checks: [Dependency vulnerabilities / SAST / secrets detection — list what applies] Blocking on: Critical and High severity findings Non-blocking on: Medium and Low (flagged, not blocking) Trigger: Every commit to main

How to handle a flagged vulnerability:

  1. Check if a fix is available — upgrade the dependency
  2. If no fix available, open a security ticket and add a suppression with justification
  3. Never suppress without a ticket and owner

Stage 5 — Build Artefact

What is produced: [Docker image / binary / zip — be specific] Registry: [ECR / GCR / Docker Hub / Artifactory — URL] Tagging convention: [service-name]:[git-sha] (also tagged :latest on main) Trigger: Commits to main only (not feature branches)


Stage 6 — Deploy to Staging

Deployment method: [e.g. Helm upgrade / kubectl apply / ecs deploy / Terraform apply] Staging URL: [URL] Trigger: Automatic on successful artefact build from main Who can deploy to staging: Any engineer (automatic)

Environment variables: Managed in [Vault / AWS SSM / GitHub Secrets / etc.] Staging is not production: [Any differences in config, scale, or data — state them here]


Stage 7 — Smoke Tests (Staging)

What runs: [Description — e.g. "10 critical path tests covering login, core API endpoints, and payment flow"] Tool: [e.g. Playwright / Postman / custom script] Pass criteria: All smoke tests pass within [X seconds] timeout Blocking: Yes — production deploy will not proceed if smoke tests fail

Smoke test suite location: [Link to test files or folder]


Stage 8 — Manual Approval Gate

Required for: [Production deploys / deploys affecting >X% of traffic / deploys to specific regions] Who can approve: [e.g. Any engineer on the team / Lead engineer / On-call engineer] Approval timeout: [e.g. 24 hours — auto-cancelled if no approval] How to approve: [GitHub Actions approve step / Slack command / other — with link]

When to withhold approval:

  • Active incident in production
  • Deploy is outside the deployment window (see below)
  • On-call engineer has not been notified

Stage 9 — Deploy to Production

Deployment method: [Same as staging or different — specify] Deployment window: [e.g. Monday–Thursday 09:00–16:00 UTC — no deploys on Fridays or before bank holidays] Canary / progressive rollout: [Yes — X% initial traffic, full rollout after Y minutes / No — full deploy] Deployment notifications: [Slack channel — #deployments]

Who is on-call during deploy: Deploying engineer is responsible until post-deploy checks pass.


Stage 10 — Post-Deploy Checks

Automated checks (run for [X minutes] after deploy):

  • [ ] Error rate: <[X]% (baseline: [Y]%)
  • [ ] P99 latency: <[X]ms (baseline: [Y]ms)
  • [ ] [Key business metric]: within [X]% of baseline

Where to watch: [Datadog / Grafana / CloudWatch dashboard — link]

If a check fails: See Rollback Procedure below.


Environments

| Environment | Purpose | Deploy trigger | URL | Data | |---|---|---|---|---| | Dev | Local development | Manual | localhost | Seeded test data | | Staging | Pre-production validation | Automatic (main) | [URL] | Anonymised prod copy | | Production | Live traffic | Manual approval | [URL] | Live data |


Branching Strategy

Model: [Trunk-based / GitFlow / GitHub Flow — describe briefly]

| Branch | Purpose | Who merges | Deploy target | |---|---|---|---| | main | Production-ready code | PR + review | Staging → Production | | feature/* | Feature development | Author | None (CI only) | | hotfix/* | Critical production fixes | Lead engineer | Can bypass staging gate with approval |

Hotfix process: [Describe when and how to use a hotfix branch — what level of incident justifies bypassing the standard process]


Rollback Procedure

Automated rollback: [Yes — triggered if post-deploy error rate exceeds [X]% / No — manual only]

Manual rollback steps:

# 1. Identify the last known good image tag
[command to list recent deployments]

# 2. Deploy the previous version
[deployment command with previous tag]

# 3. Confirm rollback is live
[smoke test command or health check URL]

# 4. Notify the team
[Slack command or template]

Rollback decision authority: Any engineer on-call can initiate a rollback without waiting for approval.

After a rollback:

  1. Create a post-deploy incident report (see [incident-postmortem skill])
  2. Do not re-deploy the same commit without fixing the root cause
  3. Notify [stakeholder / support team] of the rollback and expected fix timeline

Secrets and Configuration Management

Secret store: [Vault / AWS SSM / GitHub Secrets / Doppler — specify] How to add a new secret:

  1. [Step 1]
  2. [Step 2] Who has access: [Role or team] Rotation policy: [How often secrets are rotated and who owns it]

Never do: Commit secrets to source control, even in .env files. The pipeline includes secret scanning (Stage 4) which will flag this.


Common Failures and Fixes

| Failure | Likely cause | Fix | |---|---|---| | Build fails with "module not found" | Dependency not installed | Run [install command] and commit lock file | | Integration tests timeout | Test DB not seeded / external service down | Check [service] status; re-run pipeline | | Smoke tests fail after staging deploy | Environment variable missing | Check [config location]; compare staging and prod env vars | | Production deploy stuck at approval | Approver not notified | Tag @[on-call handle] in #deployments | | Post-deploy error rate spike | Bad deploy / upstream dependency | Check [dashboard]; initiate rollback if >5 min |


On-Call Responsibilities During Deploy

  • The deploying engineer is responsible for monitoring post-deploy checks for [X minutes] after a production deploy
  • If you cannot monitor after deploying, hand off explicitly to another engineer in #deployments
  • For deploys outside business hours: only hotfixes — always page the on-call engineer before deploying

Anti-Patterns

  • [ ] Do not describe a rollback procedure that has never been tested — a theoretical rollback is not a rollback plan; test it in staging before production
  • [ ] Do not allow deploys on Fridays or before holidays without an explicit on-call engineer who will monitor through the weekend
  • [ ] Do not commit secrets to source control even in non-production branches — secret scanning in the pipeline catches this, but prevention is the standard
  • [ ] Do not skip post-deploy monitoring after a production deploy — the deploying engineer must watch error rates and latency for the specified observation window
  • [ ] Do not suppress a security scan finding without a linked ticket and a named owner — suppressions without accountability accumulate into unmanaged risk

Quality Checks

  • [ ] Every stage has a clear owner when it fails
  • [ ] Rollback procedure is tested — not theoretical
  • [ ] Secrets management section names the actual tool used (not "use secrets management")
  • [ ] Deployment window is specific — not "during business hours"
  • [ ] Post-deploy check thresholds are calibrated to actual baseline metrics

Related Skills

View on GitHub
GitHub Stars1.4k
CategoryAutomation
Updated7d ago
Forks249

Languages

HTML

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions