Ci Cd Pipeline Builder

Community

borghei

ci-cd-pipeline-builder

Design and generate CI/CD pipelines from project stack signals across GitHub Actions, GitLab CI, CircleCI, and Buildkite. Use when bootstrapping CI, migrating pipelines, adding deployment gates, or optimizing build times.

Overview

Publisher	borghei
Repository	`Claude-Skills`
Skill name	`ci-cd-pipeline-builder`
Stars	856
Forks	154
Bundled files	5
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
5 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by borghei on GitHub. Read the source before you install it.

Installation

Install the Ci Cd Pipeline Builder AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/borghei/Claude-Skills/tree/main/engineering/ci-cd-pipeline-builder
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/borghei/Claude-Skills.git /tmp/Claude-Skills
mkdir -p .claude/skills
cp -r /tmp/Claude-Skills/engineering/ci-cd-pipeline-builder .claude/skills/ci-cd-pipeline-builder

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ci Cd Pipeline Builder in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Ci Cd Pipeline Builder on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Ci Cd Pipeline Builder is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

CI/CD Pipeline Builder

Generate production-grade CI/CD pipelines from detected project stack signals. Analyzes lockfiles, manifests, and scripts to produce optimized pipelines with proper caching, matrix strategies, security scanning, and deployment gates. Supports GitHub Actions, GitLab CI, CircleCI, and Buildkite with deployment strategies including blue-green, canary, and rolling updates.

Keywords: CI/CD, GitHub Actions, GitLab CI, pipeline, deployment, caching, matrix builds, blue-green deployment, canary deployment, security scanning, SAST, container builds, environment gates

Core Capabilities

Stack detection — infer language/runtime, package manager, build/test/lint commands, framework, and infrastructure (Docker, K8s, Terraform) from lockfiles and manifests.
Pipeline generation — lint/test/build/deploy stages with correct dependencies, caching, matrix builds, artifact passing, and conditional execution.
Deployment strategies — blue-green, canary, rolling updates, recreate, feature-flag integration, and manual approval gates.
Security integration — SAST (CodeQL, Semgrep, Snyk), dependency and container scanning (Trivy, Grype), secret scanning, and SBOM generation.
Optimization — caching matched to package manager, path filtering, concurrency control, and fail-fast matrices.

When to Use

Bootstrapping CI/CD for a new repository
Migrating between CI platforms
Optimizing slow or flaky pipelines
Adding deployment stages to an existing CI-only pipeline
Implementing security scanning in the pipeline
Setting up multi-environment deployment (staging, production)

Clarify First

Before generating the pipeline, confirm these inputs. If any is unknown or vague, ASK — do not assume:

Target platform — GitHub Actions, GitLab CI, CircleCI, or Buildkite (sets the YAML dialect pipeline_generator.py emits via --platform)
Project stack — language/runtime, package manager, and whether Docker/K8s/Terraform are present (drives stack detection, caching, and which stages are generated)
Deployment strategy & gates — blue-green, canary, rolling, or CI-only, plus any manual approval gates (determines the deploy stages and conditions)

Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.

Tools

Tool	Purpose	Command
`pipeline_generator.py`	Generate pipeline YAML from project stack detection	`python scripts/pipeline_generator.py . --platform github --deploy`
`cache_optimizer.py`	Analyze pipeline configs and suggest caching improvements	`python scripts/cache_optimizer.py --dir . --severity high`
`pipeline_linter.py`	Lint pipeline YAML for common issues	`python scripts/pipeline_linter.py --dir . --severity warning`

References

Load the reference that matches the task — keep this file lean and pull detail on demand:

references/pipeline-templates.md — stack-detection heuristics, full GitHub Actions templates (Node.js/pnpm/Next.js and Python/uv/FastAPI), the GitLab CI equivalent, the caching strategy reference table, pipeline optimization techniques, and the deployment-strategy decision framework. Read when generating a pipeline or choosing a deployment strategy.
references/quality-and-operations.md — pre-merge validation checklist, common pitfalls, best practices, troubleshooting table, and success criteria. Read before merging a generated pipeline or when one misbehaves.

Scope & Limitations

This skill covers:

Generating CI/CD pipelines for GitHub Actions, GitLab CI, CircleCI, and Buildkite
Stack detection from lockfiles, manifests, Dockerfiles, and infrastructure-as-code definitions
Deployment strategy selection (blue-green, canary, rolling, recreate) with decision framework
Pipeline optimization including caching, matrix builds, path filtering, and concurrency control

This skill does NOT cover:

Runtime infrastructure provisioning or cloud resource management (see engineering/saas-scaffolder)
Application-level security hardening beyond CI-integrated scanning (see engineering/skill-security-auditor)
Monitoring, alerting, and observability configuration after deployment (see engineering/observability-designer)
Database migration orchestration during deployments (see engineering/migration-architect)

Integration Points

Skill	Integration	Data Flow
`engineering/dependency-auditor`	Feeds vulnerability scan results into pipeline security gates	Auditor findings trigger pipeline failure or warning annotations
`engineering/release-manager`	Coordinates versioning and changelog with deploy stages	Release tags drive conditional deployment job execution
`engineering/observability-designer`	Post-deploy health checks and alerting complement pipeline gates	Pipeline triggers smoke tests; observability confirms deployment health
`engineering/env-secrets-manager`	Manages secrets referenced by pipeline environment variables	Secret rotation policies feed into pipeline secret store configuration
`engineering/migration-architect`	Database migrations run as a pre-deploy step in the pipeline	Migration status gates the application deployment job
`engineering/runbook-generator`	Generates rollback runbooks aligned with deployment strategy	Pipeline failure triggers link to the relevant rollback runbook

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

references/pipeline-templates.md10 KB
references/quality-and-operations.md4 KB
scripts/cache_optimizer.py16 KB
scripts/pipeline_generator.py17 KB
scripts/pipeline_linter.py14 KB

Frequently asked questions

What does the Ci Cd Pipeline Builder AI skill do?

Why use Ci Cd Pipeline Builder on TypingMind?

Because you install it once and use it with any model. Ci Cd Pipeline Builder is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Ci Cd Pipeline Builder in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/borghei/Claude-Skills/tree/main/engineering/ci-cd-pipeline-builder. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Ci Cd Pipeline Builder?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Ci Cd Pipeline Builder?

As many as you like. As long as a model supports skills, you can use Ci Cd Pipeline Builder with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Ci Cd Pipeline Builder AI skill free?

It is published on GitHub by borghei. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Qdrant

NousResearch

OrganizationPopular

Vector search engine for production RAG systems.

Tensorrt Llm

High-throughput LLM inference on NVIDIA GPUs.

Internal Comms

A set of resources to help me write all kinds of internal communications, using the formats that my company likes to use. Claude should use this skill whenever asked to write some sort of internal…

Claude Opus 4 5 Migration

anthropics

OrganizationPopular

Migrate prompts and code from Claude Sonnet 4.0, Sonnet 4.5, or Opus 4.1 to Opus 4.5. Use when the user wants to update their codebase, prompts, or API calls to use Opus 4.5. Handles model string…

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

CI/CD Pipeline Builder

Core Capabilities

When to Use

Clarify First

Tools

References

Scope & Limitations

Integration Points

Bundled files

Frequently asked questions

Related AI Skills

Set up your own AI workspace now