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ci-cd-pipeline-builder

Generate pragmatic CI/CD pipelines from detected project stack signals — fast baseline generation, repeatable checks, environment-aware deployment stages. Use when setting up CI for a new project, refactoring existing pipelines, or standardizing deployment workflows across multiple repos.

DeepseekModel Curated skill Quality Excellent · 90 v1.0.0

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Download .skill Standard format with system_prompt and model_config, ready for any agent framework
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name ci-cd-pipeline-builder description Generate pragmatic CI/CD pipelines from detected project stack signals — fast baseline generation, repeatable checks, environment-aware deployment stages. Use when setting up CI for a new project, refactoring existing pipelines, or standardizing deployment workflows across multiple repos. CI/CD Pipeline Builder Tier: POWERFUL Category: Engineering Domain: DevOps / Automation Overview Use this skill to generate pragmatic CI/CD pipelines from detected project stack signals, not guesswork. It focuses on fast baseline generation, repeatable checks, and environment-aware deployment stages. Core Capabilities Detect language/runtime/tooling from repository files Recommend CI stages ( lint , test , build , deploy ) Generate GitHub Actions or GitLab CI starter pipelines Include caching and matrix strategy based on detected stack Emit machine-readable detection output for automation Keep pipeline logic aligned with project lockfiles and build commands When to Use Bootstrapping CI for a new repository Replacing brittle copied pipeline files Migrating between GitHub Actions and GitLab CI Auditing whether pipeline steps match actual stack Creating a reproducible baseline before custom hardening Key Workflows 1. Detect Stack python3 scripts/stack_detector.py --repo . --format text python3 scripts/stack_detector.py --repo . --format json > detected-stack.json Supports input via stdin or --input file for offline analysis payloads. 2. Generate Pipeline From Detection python3 scripts/pipeline_generator.py \ --input detected-stack.json \ --platform github \ --output .github/workflows/ci.yml \ --format text Or end-to-end from repo directly: python3 scripts/pipeline_generator.py --repo . --platform gitlab --output .gitlab-ci.yml 3. Validate Before Merge Confirm commands exist in project ( test , lint , build ). Run generated pipeline locally where possible. Ensure required secrets/env vars are documented. Keep deploy jobs gated by protected branches/environments. 4. Add Deployment Stages Safely Start with CI-only ( lint/test/build ). Add staging deploy with explicit environment context. Add production deploy with manual gate/approval. Keep rollout/rollback commands explicit and auditable. Script Interfaces python3 scripts/stack_detector.py --help Detects stack signals from repository files Reads optional JSON input from stdin/ --input python3 scripts/pipeline_generator.py --help Generates GitHub/GitLab YAML from detection payload Writes to stdout or --output References references/pipeline-design-notes.md — common pitfalls, best practices, detection heuristics, generation strategy, platform decision notes, pre-merge validation checklist, and scaling guidance references/github-actions-templates.md references/gitlab-ci-templates.md references/deployment-gates.md README.md
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The downloaded .skill package contains the following fields.
Field Description
formatFormat tag (skill/v1)
skill_idUnique skill ID
nameSkill name
versionVersion
descriptionDescription
categoryCategories (array)
trigger_wordsTrigger words
tagsTags
sourceSource
source_urlSource URL (this page)
exported_atExported at (set per download)
system_promptSystem prompt body
model_configModel config: provider / model / temperature / max_tokens / top_p
examplesExamples
install_guideImport guide for Coze / Dify / Claude / custom frameworks
The same skill can be exported in different platform formats.
.skill Standard format with system_prompt and model_config, ready for any agent framework Download
.skillpro Enhanced format with scripts, tools, dependencies and hooks Download
.json Plain JSON export with system_prompt and model parameters only Download
Coze Markdown with frontmatter, for Coze platform import Download
Dify Dify DSL, import directly after creating an app Download

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