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5 个仓库

Awesome GitHub RepositoriesCode Workflow Executions

Executes a multi-step automated workflow that processes code through a series of actions.

Distinct from Autonomous Coding Workflows: Distinct from Autonomous Coding Workflows: focuses on executing a predefined sequence of actions rather than autonomous LLM-driven iteration.

Explore 5 awesome GitHub repositories matching development tools & productivity · Code Workflow Executions. Refine with filters or upvote what's useful.

Awesome Code Workflow Executions GitHub Repositories

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  • j3ssie/osmedeusj3ssie 的头像

    j3ssie/Osmedeus

    6,425在 GitHub 上查看↗

    Osmedeus is a security workflow orchestration engine that coordinates AI agents, shell commands, and scanning tools through declarative YAML pipelines. It functions as a distributed security scanner, a declarative workflow automator, and an AI agent framework for security, enabling automated multi-step security analysis with conditional branching, parallel execution, and distributed workers. The engine distinguishes itself through a hybrid runner model that executes workflow steps on the local host, inside Docker containers, or over SSH to remote machines, selected per step or module. It supp

    Executes Python or TypeScript code snippets defined directly within workflow definitions.

    Go
    在 GitHub 上查看↗6,425
  • olimorris/codecompanion.nvimolimorris 的头像

    olimorris/codecompanion.nvim

    6,166在 GitHub 上查看↗

    CodeCompanion is a Neovim plugin that brings large language model capabilities directly into the editor, enabling turn-based conversations with AI models in a dedicated chat buffer. It provides a comprehensive interface for interacting with LLMs, supporting multiple providers through a flexible adapter system that can route requests to various hosted or local language model services. The plugin distinguishes itself through its extensive context-sharing capabilities, allowing users to send buffer contents, visual selections, git diffs, LSP diagnostics, terminal output, quickfix lists, and view

    Executes a multi-step automated workflow that processes code through a series of actions.

    Luaacpagent-client-protocolanthropic
    在 GitHub 上查看↗6,166
  • chriswiles/claude-code-showcaseChrisWiles 的头像

    ChrisWiles/claude-code-showcase

    5,352在 GitHub 上查看↗

    This is a curated gallery of real-world workflows demonstrating how to use Claude Code for AI-driven coding, debugging, and development automation. The showcase includes executable scripts that reproduce each AI interaction locally, allowing you to see exactly how the assistant generates, explains, and modifies code within a development environment. The project shows how to build custom AI agents with targeted prompts and multi-step slash commands, define project-wide memory that persists across sessions, and inject domain-specific knowledge through markdown files. It also demonstrates integr

    Serves as a curated gallery of real-world, executable workflows demonstrating Claude Code's AI-driven development capabilities.

    JavaScript
    在 GitHub 上查看↗5,352
  • actions/github-scriptactions 的头像

    actions/github-script

    4,975在 GitHub 上查看↗

    github-script is a GitHub Actions JavaScript runner that executes asynchronous scripts to interact with the GitHub API. It serves as a JavaScript workflow scripting runtime and API client, providing a pre-configured authenticated client for automating tasks within GitHub Actions pipelines. The project enables the implementation of custom workflow logic that exceeds standard YAML syntax, including the ability to perform REST API calls and execute GraphQL queries for complex data extraction. It supports the management of multiple authenticated clients to facilitate cross-organization repository

    Runs asynchronous code to interact with remote services using authenticated clients and shared context.

    TypeScript
    在 GitHub 上查看↗4,975
  • parcadei/continuous-claude-v3parcadei 的头像

    parcadei/Continuous-Claude-v3

    3,531在 GitHub 上查看↗

    This project is an agentic development framework and autonomous software engineering system. It utilizes a coordinated network of specialized LLM agents to automate the full software development lifecycle, from codebase exploration and architectural planning to implementation and automated refactoring. The system is distinguished by an agentic memory system and a test-driven development orchestrator. It maintains project continuity across sessions by capturing architectural learnings and state in a persistent semantic database and enforces code quality through an automated cycle of generating

    Executes small code tweaks and syntax corrections without requiring a full test-driven development process.

    Pythonagentsclaude-codeclaude-code-cli
    在 GitHub 上查看↗3,531
  1. Home
  2. Development Tools & Productivity
  3. Agentic Workflow Integrations
  4. Autonomous Coding Workflows
  5. Code Workflow Executions

探索子标签

  • Asynchronous Script WorkflowsExecution of multi-step asynchronous scripts that maintain shared context and authenticated sessions. **Distinct from Code Workflow Executions:** Distinct from Code Workflow Executions: focuses on the asynchronous JavaScript execution model rather than a sequence of autonomous coding actions.
  • Inline Script ExecutionsExecutes Python or TypeScript code snippets defined directly within workflow definitions. **Distinct from Code Workflow Executions:** Distinct from Code Workflow Executions: focuses on executing inline code snippets, not multi-step code processing workflows.
  • Quick Fix ExecutionsSmall, low-risk automated code adjustments and syntax corrections that bypass full test-driven cycles. **Distinct from Code Workflow Executions:** Distinct from Code Workflow Executions: focuses on minimal, single-purpose syntax or logic tweaks rather than complex multi-step workflows.
  • Workflow GalleriesCurated collections of executable workflow examples that demonstrate AI-driven coding, debugging, and automation patterns. **Distinct from Code Workflow Executions:** Distinct from Code Workflow Executions: focuses on showcasing and documenting workflows as runnable examples rather than executing a single predefined sequence.