github-workflow-automation
AI-driven GitHub Actions automation featuring swarm-based workflow orchestration, intelligent CI/CD pipeline management, and autonomous repository maintenance.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
167 skills found
AI-driven GitHub Actions automation featuring swarm-based workflow orchestration, intelligent CI/CD pipeline management, and autonomous repository maintenance.
Autonomous improvement loop for codebase optimization. Automatically modifies, measures, and iterates on code based on a specific goal and mechanical metric.
AI-assisted version control for code agents. Track prompts, context, and diffs automatically with MemoV to ensure full traceability without polluting your git history.
Standardizes project context by managing artifacts (product, tech-stack, workflow, tracks) in a conductor/ directory. Supports project scaffolding, artifact synchronization, and AI alignment for greenfield and brownfield projects.
Create robust, scalable, and maintainable technical implementation plans for complex software projects.
World-class senior data engineering skill for building scalable data pipelines, ETL/ELT systems, and modern data infrastructure using Python, Spark, dbt, and Kafka.
Scaffold complex, multi-step coding tasks into actionable implementation plans and execute them autonomously using a Claude-driven bash loop.
Create structured, high-quality technical implementation plans via an agent-driven, iterative process. Ideal for complex refactoring, new features, and technical design.
Structured 6-phase workflow for planning and implementing features, skills, and architectural changes with automated tool discovery and safety verification.
Multi-perspective AI consultation for technical architecture, complex refactoring, and structured debugging.
Execute implementation plans in small, verifiable batches with pause-for-feedback checkpoints to prevent drift and ensure code quality.
A comprehensive framework for creating, structuring, and managing reusable AI Agent Skills to standardize instruction-driven workflows.