Expert guide for building CI/CD pipelines with GitHub Actions, Vercel, and other platforms. Use when automating builds, tests, deployments, or release workflows.
4979 个结果
(38.0ms)
页 28 / 249
V3 CLI Modernization
0.00
CLI modernization and hooks system enhancement for claude-flow v3. Implements interactive prompts, command decomposition, enhanced hooks integration, and intelligent workflow automation.
llm_evaluation
0.00
Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking. Use when testing LLM performance, measuring AI application quality, or...
llm_evaluation
0.00
Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking. Use when testing LLM performance, measuring AI application quality, or...
backend-dev
0.00
Comprehensive backend development workflow that orchestrates expert analysis, architecture design, implementation, and deployment using the integrated toolset. Handles everything from API design...
backend-dev
0.00
Comprehensive backend development workflow that orchestrates expert analysis, architecture design, implementation, and deployment using the integrated toolset. Handles everything from API design...
creating-workflows
0.00
Use this skill when creating automated multi-phase workflows for development tasks using claude-flow orchestration. Implements patterns for implementation kickoff, verification, retry loops, and...
semantic-versioning
0.00
Implement semantic versioning (SemVer) with automated release management. Use conventional commits, semantic-release, and version bumping strategies.
Comprehensive web application reconnaissance and mapping coordinator that orchestrates passive browsing, active endpoint discovery, attack surface analysis, and headless browser automation for...
execute-plan
0.00
Smart orchestrator for chunked plans - auto-detects complexity, recommends execution mode (parallel/automated/supervised/hybrid), dispatches to executor, tracks progress with mandatory code...
llm-evaluation
0.00
Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking. Use when testing LLM performance, measuring AI application quality, or...
llm-evaluation
0.00
Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking. Use when testing LLM performance, measuring AI application quality, or...
llm-evaluation
0.00
Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking. Use when testing LLM performance, measuring AI application quality, or...
llm-evaluation
0.00
Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking. Use when testing LLM performance, measuring AI application quality, or...
llm-evaluation
0.00
Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking. Use when testing LLM performance, measuring AI application quality, or...
ml-pipeline-workflow
0.00
Build end-to-end MLOps pipelines from data preparation through model training, validation, and production deployment. Use when creating ML pipelines, implementing MLOps practices, or automating...
ml-pipeline-workflow
0.00
Build end-to-end MLOps pipelines from data preparation through model training, validation, and production deployment. Use when creating ML pipelines, implementing MLOps practices, or automating...
ml-pipeline-workflow
0.00
Build end-to-end MLOps pipelines from data preparation through model training, validation, and production deployment. Use when creating ML pipelines, implementing MLOps practices, or automating...
ml-pipeline-workflow
0.00
Build end-to-end MLOps pipelines from data preparation through model training, validation, and production deployment. Use when creating ML pipelines, implementing MLOps practices, or automating...
codex
0.00
Execute Codex CLI for code analysis, refactoring, and automated code changes. Use when you need to delegate complex code tasks to Codex AI with file references (@syntax) and structured output.