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概要と使いどころ
Design, implement, and validate reproducible machine-learning pipelines spanning data preparation, training, evaluation, registry, and deployment gates. Use when the user requests an ML pipeline, needs to turn model scripts into an orchestrated workflow, or provides pipeline components that must be connected safely.
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Internal — for Boundless team members only. Monitor Boundless deployment pipelines (AWS CodePipeline + CodeBuild) on the ops account. Use when the user wants to track a deployment after merging a PR, check whether a commit has rolled out to staging/prod, diagnose a failed deployment, watch the status of a specific pipeline, or get prompted to approve a production rollout once staging succeeds. Do NOT use for service runtime debugging (use ops-logs-query) or for deploying dev infrastructure (use ops-infra-deploy).
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Design CI/CD pipelines that run test suites. Covers GitHub Actions and GitLab CI templates, parallelism and sharding, artifact management, flaky-test quarantine, test-result publishing, coverage quality gates, OIDC keyless deploy, and copy-paste workflows for Playwright, Jest, and multi-stage pipelines. Use when: "CI/CD," "GitHub Actions," "pipeline," "test in CI," "GitLab CI," "continuous integration," "test automation pipeline," "shard tests in CI." Not for: per-test flaky healing at runtime — use test-reliability; go/no-go release decisions and smoke-test checklists — use release-readiness; test-result dashboards and trend reporting — use qa-metrics. Related: playwright-automation, qa-metrics, test-reliability, coverage-analysis, release-readiness.
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World-class continuous integration and deployment - GitHub Actions, GitLab CI, deployment strategies, and the battle scars from pipelines that broke productionUse when "ci/cd, cicd, pipeline, github actions, gitlab ci, circleci, jenkins, workflow, deployment, deploy, release, blue green, canary, rollback, build, test automation, continuous integration, continuous deployment, cicd, github-actions, gitlab-ci, deployment, automation, devops, pipelines, continuous-integration, continuous-deployment" mentioned.
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Manage repositories, pipelines, and code review with Bitbucket Cloud. Use when a user asks to set up Bitbucket repositories, configure Bitbucket Pipelines for CI/CD, manage pull requests, set up branch permissions, use Bitbucket REST API 2.0, create webhooks, manage deployment environments, set up code review workflows, integrate with Jira, configure merge checks, or automate repository operations. Covers repository management, CI/CD pipelines, code review, deployments, and Atlassian ecosystem integration.
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Build a data pipeline — ETL/ELT with extraction, transformation, loading, error handling, and scheduling. Use when asked to "build ETL", "data pipeline", "move data from X to Y", or "sync data".
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Design or audit B2B sales pipeline — define stage names, entry/exit criteria, qualification standards, and CRM field requirements. Use when asked to "design our pipeline", "audit our CRM stages", "define what qualified means", or "build a sales process".
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Provides CI/CD pipeline best practices for GitHub Actions, deployment strategies, and pipeline optimization. Use when setting up pipelines, configuring GitHub Actions, managing deployments, or when user mentions 'CI', 'CD', 'pipeline', 'GitHub Actions', 'deploy', 'workflow', 'build'.
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Audit a MaaFramework/Maa-series project's Git history to learn how Pipeline JSON, interface options, Python AgentServer CustomAction code, and related data tables evolved. Use when asked to review a Maa project from initial commit through a target commit, map `action: Custom` pipeline nodes to `@AgentServer.custom_action(...)` implementations, find pipeline/custom/option patterns or breakages, and produce a report plus skill-improvement recommendations.
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Universal Pipeline JSON 编写指南。基于 MaaFramework Pipeline 协议，提供节点命名、识别算法、动作类型、流程控制、可复用节点等编码规范与模式参考。在编写、修改或审查 Pipeline JSON、设计节点流程、使用 TemplateMatch/OCR/Custom 识别或 Click/Swipe 动作时使用。
日本語の概要は準備中です。原文の説明を表示しています。
生成 MaaFramework Pipeline 项目的可交互状态机图谱。当用户想"看 Pipeline 节点关系"、"画状态机图"、"画 Mermaid 图"、"看 node 间关系"、"找孤立节点 / orphan node"、"看 Python 怎么驱动 Pipeline"、"看 interface.json 入口"、"调试跨文件 next 引用"、"重构前理清架构" 时使用。**任何涉及 MaaFramework 节点关系可视化的需求都用这个 skill**,即便用户没明确说"画图"。
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Manages AWS CodePipeline stages and actions using AWS SDK for JavaScript (CodePipeline, CodeBuild, CodeDeploy APIs). Automates blue-green deployments and cross-account pipeline configurations.
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Run the viz pipeline to render icons from existing glyphs. Entry point for the viz subproject covering palette generation, data building, manifest creation, and icon rendering for skills, agents, and teams. Always use build.sh as the pipeline entry point — never call Rscript directly.
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Orchestrate end-to-end machine learning pipelines using Prefect or Airflow with DAG construction, task dependencies, retry logic, scheduling, monitoring, and integration with MLflow, DVC, and feature stores for production ML workflows. Use when automating multi-step ML workflows from data ingestion to deployment, scheduling periodic model retraining, coordinating distributed training tasks, or managing retry logic and failure recovery across pipeline stages.
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Design and implement multi-stage CI/CD pipelines using GitHub Actions with matrix builds, dependency caching, artifact management, and secret handling. Create workflows that span linting, testing, building, and deployment stages with parallel execution and conditional logic. Use when setting up automated testing and deployment for a new project, migrating from Jenkins or CircleCI to GitHub Actions, implementing matrix builds across platforms, adding build caching, or creating multi-stage pipelines with security scanning and quality gates.
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Parallel SDLC batch runner. Analyzes a list of independent task descriptions, groups them by heuristic file-conflict prediction, dispatches one worktree-isolated background agent per task (each running the full pipeline-orchestrator: BA → Dev → QA → Sec → Docs), and aggregates results into a single batch summary. Use when: - `/sdlc:batch` invokes this skill after parsing its arguments (Step 2 of commands/batch.md) - You have 2+ independent feature/fix descriptions to run through the SDLC pipeline in parallel Do NOT use for: - A single task (use pipeline-orchestrator directly via /sdlc:start) - Tasks that must share a single working tree (this skill isolates each task in its own git worktree)
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Phase 5 of the feature-pipeline suite. Use this after /fp-iterate prints the M4 stop hook confirming CI is green. Fetches origin/main, runs gaia dev diff to surface any skill-registry changes the PR introduced that are unrelated to its stated purpose (accidental drift), then prints the final pipeline summary including a CI churn report (via /ci-churn). Also invoke standalone whenever you want to audit whether a branch has unexpected registry drift — e.g. before merging any review/meta or cli/ branch, or when a reviewer asks "did this PR touch anything it shouldn't?". Triggers: "check for drift", "drift check", "final summary", "pipeline done", "wrap up the pipeline", "fp-drift", "Phase 5".
日本語の概要は準備中です。原文の説明を表示しています。
Execute ENCODE RNA-seq pipeline from FASTQ to gene quantification and signal tracks. Child of pipeline-guide. Provides Nextflow execution with Docker and cloud deployment. Use when processing RNA-seq data with STAR alignment, RSEM/Kallisto quantification, or generating expression matrices. Trigger on: RNA-seq pipeline, gene expression, STAR alignment, RSEM quantification, transcript quantification, TPM, FPKM, RNA processing, run RNA-seq.
日本語の概要は準備中です。原文の説明を表示しています。
Execute CUT&RUN processing pipeline from FASTQ to peaks and signal tracks. Child of pipeline-guide. Provides Nextflow execution with Docker and cloud deployment. Use when processing CUT&RUN or CUT&Tag data, an alternative to ChIP-seq with lower background. Trigger on: CUT&RUN pipeline, CUT&Tag, SEACR, Henikoff, targeted chromatin, pA-MNase, process CUT&RUN.
日本語の概要は準備中です。原文の説明を表示しています。
Execute ENCODE DNase-seq pipeline from FASTQ to hotspots and footprints. Child of pipeline-guide. Provides Nextflow execution with Docker and cloud deployment. Use when processing DNase-seq data, calling DNase hypersensitive sites, performing footprinting analysis. Trigger on: DNase-seq pipeline, DNase hypersensitive, DHS, Hotspot2, footprinting, DNase I, chromatin accessibility DNase.
日本語の概要は準備中です。原文の説明を表示しています。
Execute ENCODE ChIP-seq processing pipeline from FASTQ to peaks and signal tracks. Child of pipeline-guide. Provides stage-by-stage Nextflow execution with Docker containers and cloud deployment. Use when users need to process ChIP-seq data following ENCODE standards, run peak calling with MACS2, perform IDR analysis, or generate signal tracks. Trigger on: ChIP-seq pipeline, run ChIP-seq, process ChIP-seq, MACS2 peak calling, IDR analysis, ChIP-seq FASTQ processing.
日本語の概要は準備中です。原文の説明を表示しています。
Execute ENCODE Hi-C pipeline from FASTQ to contact matrices and loop calls. Child of pipeline-guide. Provides Nextflow execution with Docker and cloud deployment. Use when processing Hi-C data, generating contact matrices, or calling loops. Trigger on: Hi-C pipeline, chromatin conformation, contact matrix, loop calling, TAD detection, Juicer, HiCCUPS, 3D genome.
日本語の概要は準備中です。原文の説明を表示しています。
Execute ENCODE ATAC-seq processing pipeline from FASTQ to peaks and signal tracks. Child of pipeline-guide. Provides stage-by-stage Nextflow execution with Docker containers and cloud deployment. Handles Tn5 transposase offset correction, mitochondrial read removal, and nucleosome-free fragment selection. Use when users need to process ATAC-seq data following ENCODE standards. Trigger on: ATAC-seq pipeline, run ATAC-seq, process ATAC-seq, chromatin accessibility, open chromatin, Tn5 shift, TSS enrichment.
日本語の概要は準備中です。原文の説明を表示しています。
Write an ETL operational runbook. Use when the user says "ETL runbook", "pipeline runbook", "data job runbook", "how to operate this ETL", "on-call guide for data pipelines", "what to do when the data job fails", "pipeline troubleshooting guide", "data ops runbook", or needs to document how to operate, monitor, and recover a data pipeline or ETL job - even if they don't explicitly say "runbook".
日本語の概要は準備中です。原文の説明を表示しています。