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ai-dev-loopAI 开发循环

Agent Skill

ai-dev-loop 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

2,371

周安装

95

GitHub Stars

21

下载量

768
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

3

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:ai-dev-loop(AI 开发循环)
来源仓库:https://github.com/shipshitdev/library
仓库路径:skills/ai-dev-loop
安装命令:
npx skills add https://github.com/shipshitdev/library --skill ai-dev-loop
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/shipshitdev/library --skill ai-dev-loop

简介

用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,支持自动化任务执行与质量检查。

  • 适用于多平台并行开发,包括 Claude CLI、Cursor 和 Codex 的协同工作流。
  • 通过 npx skills add 命令从指定 GitHub 仓库安装,需结合项目实际环境配置。
  • 涉及文件读写或命令执行前,建议确认权限范围和操作边界,避免误操作。
  • ai-dev-loop 属于AI 工具类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

AI Development Loop

Autonomous task execution with QA gates across multiple AI platforms.

Overview

The AI Development Loop enables fully autonomous feature development where:

  • AI agents pick up and implement tasks from a queue
  • You do QA only (approve or reject in Testing column)
  • Multiple platforms (Claude CLI, Cursor, Codex) can work in parallel
  • Rate limits are maximized by switching between platforms

Architecture

┌─────────────┐     ┌─────────────┐     ┌─────────────┐     ┌─────────────┐
│   BACKLOG   │────▶│   TO DO     │────▶│  TESTING    │────▶│    DONE     │
│             │     │             │     │             │     │             │
│  PRDs ready │     │ Agent picks │     │ YOU review  │     │  Shipped    │
│             │     │ & builds    │     │ & approve   │     │             │
└─────────────┘     └─────────────┘     └─────────────┘     └─────────────┘
                          │                   │
                    ┌─────┴─────┐       ┌─────┴─────┐
                    │  Claude   │       │  Reject   │
                    │  Cursor   │       │  → To Do  │
                    │  Codex    │       └───────────┘
                    └───────────┘

Task Lifecycle

1. Task Creation

Tasks live in .agents/TASKS/[task-name].md with structured metadata:

## Task: [Feature Name]

**ID:** feature-name-slug
**Status:** Backlog | To Do | Testing | Done
**Priority:** High | Medium | Low
**PRD:** [Link](../PRDS/prd-file.md)

### Agent Metadata

**Claimed-By:** [platform-session-id]
**Claimed-At:** [timestamp]
**Completed-At:** [timestamp]

### Progress

**Agent-Notes:** [real-time updates]
**QA-Checklist:**

- [ ] Code compiles/lints
- [ ] Tests pass (CI)
- [ ] User acceptance
- [ ] Visual review

### Rejection History

**Rejection-Count:** 0
**Rejections:** [list of rejection notes]

2. Task Claiming

When an agent runs /loop:

  1. Scans .agents/TASKS/ for Status: To Do
  2. Sorts by priority (High > Medium > Low)
  3. Skips tasks with active claims (< 30 min old)
  4. Updates task with Claimed-By and Claimed-At

3. Implementation

Agent works on the task:

  1. Reads task file and linked PRD
  2. Checks .agents/SESSIONS/ for related past work
  3. Implements the feature/fix
  4. Updates Agent-Notes with progress
  5. Creates branch and commits

4. Quality Check

Before moving to Testing:

  1. Runs qa-reviewer skill
  2. Updates QA-Checklist items
  3. Ensures code compiles/lints

5. Completion

Agent finalizes:

  1. Sets Status: Testing
  2. Sets Completed-At timestamp
  3. Adds final summary to Agent-Notes
  4. Prompts for next action

6. QA Gate (Your Turn)

In Kaiban.md:

  1. Review Testing column
  2. Click task to see PRD preview
  3. Check linked PR
  4. Approve: Drag to Done
  5. Reject: Click reject, add note → returns to To Do

7. Rejection Handling

When rejected:

  1. Status returns to To Do
  2. Rejection-Count increments
  3. Rejection note added to history
  4. Next /loop picks up with full context

Multi-Platform Strategy

Platform Strengths

PlatformBest For
Claude CLIComplex logic, backend, architecture
CursorUI components, styling, visual work
CodexBulk refactoring, migrations, docs

Parallel Execution

Multiple platforms can work simultaneously:

  • Each claims different tasks
  • Claims prevent conflicts (30-min lock)
  • Shared state via task files

Rate Limit Handling

When rate limited:

  1. Agent saves progress to Agent-Notes
  2. Releases claim (clears Claimed-By)
  3. Suggests switching platform
  4. User continues with different platform

Daily Workflow

Morning QA Session

  1. Open Kaiban.md extension in VS Code
  2. Review Testing column
  3. Approve good work → Done
  4. Reject with notes → To Do

Throughout Day

# Claude CLI
claude
> /loop   # Process task
> /loop   # Next task
# Rate limited? Switch to Cursor

Rate Limit Strategy

Claude limit? → Switch to Cursor
Cursor limit? → Switch to Codex
All limited? → QA time (review Testing)

Integration Points

Kaiban.md Extension

  • Visual Kanban board for .agents/TASKS/
  • Drag & drop status changes
  • PRD preview panel
  • Reject button with note input
  • Agent claim status badges

Existing Skills

  • qa-reviewer: 6-phase quality verification
  • session-documenter: Auto-document completed work
  • rules-capture: Learn from rejection feedback

Git Workflow

  • Branch per task: feature/[task-id]
  • Commits with clear messages
  • PR linked in task file

Not a Daemon

Important: /loop is NOT a background process.

  • Each invocation handles ONE task
  • Returns control to user
  • User decides to continue or stop
  • Respects "never run background processes" rule

Claim Expiration

Claims expire after 30 minutes:

  • Handles agent crashes
  • Handles rate limit interruptions
  • Previous Agent-Notes provide context for pickup
  • Enables multi-platform handoff

Best Practices

For Task Creation

  • Write clear, actionable task descriptions
  • Link to PRD for requirements
  • Set appropriate priority
  • Include testing criteria

For Agents

  • Read task and PRD thoroughly before starting
  • Update Agent-Notes regularly
  • Run qa-reviewer before completing
  • Create clean, focused commits

For QA (You)

  • Review PRD alongside implementation
  • Provide specific rejection feedback
  • Approve incrementally (don't batch)
  • Keep Testing column short

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Claude Code

28.54%
按下载量换算219

Gemini CLI

26.09%
按下载量换算200

Antigravity

16.73%
按下载量换算128

OpenCode

11.48%
按下载量换算88

Codex

7.63%
按下载量换算59

Cursor

3.4%
按下载量换算26

安全审计

Gen Agent Trust Hub

通过

Socket

可疑

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。

来源信息

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