Guide · Agent skill
How to use the Deployment Pipeline Design agent skill
Updated · written with AI from the project's own documentation and checked against our catalogue data
The deployment-pipeline-design skill gives an AI agent structured guidance for moving software from development to staging to production safely. It is written for engineers who design or migrate CI/CD pipelines and for developers debugging a deployment gate or canary that stalls. After this guide you will know how to install the skill, how to phrase requests that trigger it, and what to check before acting on its output.
Deployment Pipeline Designwshobson/agents · MIT Download the skill Quick start
- 1Download the ZIP. Get the deployment-pipeline-design ZIP from our page.
- 2Unzip into a skills folder. Extract it into ~/.claude/skills/ for personal use or into your project's .claude/skills/ folder.
- 3Or upload in the Claude apps. Go to Settings → Capabilities → Skills and upload the ZIP.
- 4Describe your pipeline problem. State your application type, deployment target, environments, downtime tolerance and monitoring stack in plain language.
- 5Review the proposed design. Check stages, gates and rollback steps against your own environment before making any change.
- 6Verify before production. Test sample configuration in a non-production environment first, since the skill does not deploy anything.
What is an agent skill and what does this one do?
An agent skill is a folder of instructions that an AI agent loads when a task matches the skill's description. This skill is documentation-style guidance: it shapes the agent's advice and sample configuration files, and it does not deploy anything itself.
When active, the agent can propose pipeline stages, approval gates, canary or blue-green rollout strategies, health checks, and rollback plans. It can also help debug cases where a deployment gate fails or a canary never promotes.
- Pipeline configuration: stage definitions, job dependencies, parallelism and caching strategy
- Deployment strategy: canary weights, blue-green switchover or rolling parameters
- Health checks: shallow versus deep readiness probes and post-deployment smoke test scripts
- Gate definitions: automated metric thresholds and manual approval workflows
- Rollback plan: automated triggers and manual runbook steps
How do you install the deployment-pipeline-design skill?
Download the ZIP for this skill from our page. You can install it in one of two ways.
For a personal install, unzip it into ~/.claude/skills/. To scope it to one project, unzip it into that project's .claude/skills/ folder. You can also upload the ZIP in the Claude apps under Settings → Capabilities → Skills.
- Personal: unzip into ~/.claude/skills/
- Single project: unzip into your project's .claude/skills/
- Claude apps: Settings → Capabilities → Skills, then upload the ZIP
What files come with the skill?
The skill folder contains SKILL.md, which holds the core patterns, input and output definitions, and troubleshooting notes. It also includes references/details.md with detailed patterns and worked examples, and references/advanced-strategies.md with extended YAML examples for platform-specific configurations, multi-region canary patterns and database migration rollback strategies.
The agent reads the extra reference files only when the core guidance is not enough.
- SKILL.md: core patterns and troubleshooting
- references/details.md: stage breakdown and approval gate patterns
- references/advanced-strategies.md: platform-specific and advanced rollout examples
How do you trigger the skill with a natural request?
You do not need a special command. Describe the pipeline problem in plain language and include the details the skill asks for: application type, deployment target, number of environments, acceptable downtime, rollback expectations and the monitoring stack you use.
The skill's description names these trigger situations: designing zero-downtime deployment pipelines, implementing canary rollout strategies, setting up multi-environment promotion workflows, and debugging failed deployment gates in CI/CD.
- "Design a zero-downtime pipeline for a Node service on Kubernetes with staging and production."
- "Add a canary rollout with Prometheus error-rate checks and automatic rollback."
- "Our canary never promotes to 100%. Help me find out why."
- "Set up manual approval before production with required reviewers."
What does a worked example look like?
A common failure is a canary that never promotes. The skill's troubleshooting notes say that Argo Rollouts needs a valid AnalysisTemplate to auto-promote, and that a Prometheus query returning no data leaves the analysis inconclusive and stalls promotion. The fix it suggests is to add inconclusiveLimit so the rollout fails fast instead of hanging.
The sample below comes from the skill's troubleshooting section. Check the metric name and thresholds against your own environment before applying it.
spec:
metrics:
- name: error-rate
failureCondition: "result[0] > 0.05"
inconclusiveLimit: 2 # fail after 2 inconclusive results, not hang indefinitely
provider:
prometheus:
query: |
sum(rate(http_requests_total{status=~"5.."}[2m]))
/ sum(rate(http_requests_total[2m]))What does the skill need and what are its safety limits?
The skill lists no required tools, runs no scripts and makes no network calls. It is guidance text plus sample files.
The sample YAML, Dockerfile and migration snippets are illustrative. Mistakes in pipeline or migration config can cause outages or data problems, so review every output against your own environment before use. Do not make production changes without review.
For a ready-to-run pipeline for one specific CI tool, use a more specific sibling skill such as github-actions-templates or gitlab-ci-patterns.
- Requires: nothing listed
- Runs scripts: no
- Uses network: no
- Review all sample configuration before applying it to production
What tips help you get better results?
Give the agent your real constraints up front. Acceptable downtime, approval teams and compliance scans change the design more than any other input.
For database changes, keep migrations backward-compatible for at least one release cycle, and keep undo scripts versioned with the forward migration. Avoid destructive migrations such as DROP COLUMN or ALTER NOT NULL until the old code is retired from all environments.
If a health check passes in the pipeline but production is unhealthy, ask the agent to replace a shallow /ping check with a deep readiness check that verifies real dependencies.
- Name your deployment target and environment count
- State rollback expectations explicitly
- Ask for a deep readiness check if shallow checks pass while production fails
- Check that production environment protection rules have reviewers assigned
What people use it for
- Designing a multi-stage pipeline with build, test, staging, approval and production stages
- Choosing between canary, blue-green and rolling rollouts for a Kubernetes service
- Adding required reviewers to a production environment so the approval gate does not wait indefinitely
- Diagnosing a canary stuck below 100% because its Prometheus analysis returns no data
- Planning backward-compatible database migrations alongside a rollback plan
Frequently asked questions
How do I install the deployment-pipeline-design skill?
Download the ZIP from our page. Unzip it into ~/.claude/skills/ for personal use, or into a project's .claude/skills/ folder for one project. You can also upload the ZIP in the Claude apps under Settings → Capabilities → Skills.
Does this skill deploy my application?
No. The skill is documentation-style guidance that shapes the agent's advice and sample configuration files. It does not itself deploy anything, and it runs no scripts and makes no network calls.
What do I need to use it?
The skill lists no required tools. You need an agent environment that supports skills, plus a description of your deployment target and environments so the guidance fits your setup.
Is the deployment-pipeline-design skill free?
The skill is published under the MIT licence. Check the repository's licence file for the full terms before reusing it.
Why does my canary never promote to 100%?
A common cause is an Argo Rollouts analysis that returns no data, for example after a Prometheus metric name changes. The analysis stays inconclusive and promotion stalls. Adding inconclusiveLimit makes the rollout fail fast instead of hanging.
Which skill should I use for GitHub Actions or GitLab CI?
Use github-actions-templates for GitHub Actions implementation patterns or gitlab-ci-patterns for GitLab CI/CD. This skill is better for designing the overall pipeline architecture, gates and rollout strategy.
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Our verdict
Use this skill if you are designing or migrating a CI/CD pipeline, setting up approval gates or canary rollouts, or debugging a stalled deployment, and you want an agent to reason through the design with you. Skip it if you need a ready-to-run pipeline for one CI tool, since a platform-specific sibling skill will be more direct, and do not apply its sample configuration to production without review.
Download the skill