Codex Issue Plan-Execute Workflow

Streamlined autonomous workflow for Codex that integrates issue planning, queue management, and solution execution in a single stateful Skill. Supports batch processing with minimal queue overhead and dual-agent execution strategy.

Architecture Overview

For complete architecture details, system diagrams, and design principles, see ARCHITECTURE.md.

Key concepts:

• Persistent Dual-Agent System: Two long-running agents (Planning + Execution) that maintain context across all tasks
• Sequential Pipeline: Issues → Planning Agent → Solutions → Execution Agent → Results
• Unified Results: All results accumulated in single

  planning-results.json

  and

  execution-results.json

  files
• Efficient Communication: Uses

  send_input()

  for task routing without agent recreation overhead

---

⚠️ Mandatory Prerequisites (强制前置条件)

⛔ 禁止跳过: 在执行任何操作之前，必须阅读以下两份P0规范文档。未理解规范直接执行将导致输出质量不符合标准。

Document	Purpose	When
specs/issue-handling.md	Issue 处理规范和数据结构	执行前必读
specs/solution-schema.md	解决方案数据结构和验证规则	执行前必读

---

Execution Flow

Phase 1: Initialize Persistent Agents

→ 查阅: ARCHITECTURE.md - 系统架构
→ 查阅: phases/orchestrator.md - 编排逻辑
→ Spawn Planning Agent with

prompts/planning-agent.md

(stays alive)
→ Spawn Execution Agent with

prompts/execution-agent.md

(stays alive)

Phase 2: Planning Pipeline

→ 查阅: phases/actions/action-plan.md, specs/subagent-roles.md For each issue sequentially:

1. Send issue to Planning Agent via

   send_input()

   with planning request
2. Wait for Planning Agent to return solution JSON
3. Store result in unified

   planning-results.json

   array
4. Continue to next issue (agent stays alive)

Phase 3: Execution Pipeline

→ 查阅: phases/actions/action-execute.md, specs/quality-standards.md For each successful planning result sequentially:

1. Send solution to Execution Agent via

   send_input()

   with execution request
2. Wait for Execution Agent to complete implementation and testing
3. Store result in unified

   execution-results.json

   array
4. Continue to next solution (agent stays alive)

Phase 4: Finalize

→ 查阅: phases/actions/action-complete.md → Close Planning Agent (after all issues planned) → Close Execution Agent (after all solutions executed) → Generate final report with statistics

State Schema

{
  "status": "pending|running|completed",
  "phase": "init|listing|planning|executing|complete",
  "issues": {
    "{issue_id}": {
      "id": "ISS-xxx",
      "status": "registered|planning|planned|executing|completed",
      "solution_id": "SOL-xxx-1",
      "planned_at": "ISO-8601",
      "executed_at": "ISO-8601"
    }
  },
  "queue": [
    {
      "item_id": "S-1",
      "issue_id": "ISS-xxx",
      "solution_id": "SOL-xxx-1",
      "status": "pending|executing|completed"
    }
  ],
  "context": {
    "work_dir": ".workflow/.scratchpad/...",
    "total_issues": 0,
    "completed_count": 0,
    "failed_count": 0
  },
  "errors": []
}

---

Directory Setup

const timestamp = new Date().toISOString().slice(0,19).replace(/[-:T]/g, '');
const workDir = `.workflow/.scratchpad/codex-issue-${timestamp}`;

Bash(`mkdir -p "${workDir}"`);
Bash(`mkdir -p "${workDir}/solutions"`);
Bash(`mkdir -p "${workDir}/snapshots"`);

Output Structure

.workflow/.scratchpad/codex-issue-{timestamp}/
├── planning-results.json               # All planning results in single file
│   ├── phase: "planning"
│   ├── created_at: "ISO-8601"
│   └── results: [
│       { issue_id, solution_id, status, solution, planned_at }
│     ]
├── execution-results.json              # All execution results in single file
│   ├── phase: "execution"
│   ├── created_at: "ISO-8601"
│   └── results: [
│       { issue_id, solution_id, status, commit_hash, files_modified, executed_at }
│     ]
└── final-report.md                     # Summary statistics and report

---

Reference Documents by Phase

🔧 Setup & Understanding (初始化阶段)

用于理解整个系统架构和执行流程

Document	Purpose	Key Topics
phases/orchestrator.md	编排器核心逻辑	如何管理agents、pipeline流程、状态转换
phases/state-schema.md	状态结构定义	完整状态模型、验证规则、持久化
specs/agent-roles.md	Agent角色和职责定义	Planning & Execution Agent详细说明

📋 Planning Phase (规划阶段)

执行Phase 2时查阅 - Planning逻辑和Issue处理

Document	Purpose	When to Use
phases/actions/action-plan.md	Planning流程详解	理解issue→solution转换逻辑
phases/actions/action-list.md	Issue列表处理	学习issue加载和列举逻辑
specs/issue-handling.md	Issue数据规范	理解issue结构和验证规则 ✅ 必读
specs/solution-schema.md	解决方案数据结构	了解solution JSON格式 ✅ 必读

⚙️ Execution Phase (执行阶段)

执行Phase 3时查阅 - 实现和验证逻辑

Document	Purpose	When to Use
phases/actions/action-execute.md	Execution流程详解	理解solution→implementation逻辑
specs/quality-standards.md	质量标准和验收条件	检查implementation是否达标

🏁 Completion Phase (完成阶段)

执行Phase 4时查阅 - 收尾和报告逻辑

Document	Purpose	When to Use
phases/actions/action-complete.md	完成流程	生成最终报告、统计信息

🔍 Debugging & Troubleshooting (问题排查)

遇到问题时查阅 - 快速定位和解决

Issue	Solution Document
执行过程中状态异常	phases/state-schema.md - 验证状态结构
Planning Agent输出不符合预期	phases/actions/action-plan.md + specs/solution-schema.md
Execution Agent实现失败	phases/actions/action-execute.md + specs/quality-standards.md
Issue数据格式错误	specs/issue-handling.md

📚 Architecture & Agent Definitions (架构和Agent定义)

核心设计文档

Document	Purpose	Notes
ARCHITECTURE.md	系统架构和设计原则	启动前必读
specs/agent-roles.md	Agent角色定义	Planning & Execution Agent详细职责
prompts/planning-agent.md	Planning Agent统一提示词	用于初始化Planning Agent
prompts/execution-agent.md	Execution Agent统一提示词	用于初始化Execution Agent

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Usage Examples

Batch Process Specific Issues

codex -p "@.codex/prompts/codex-issue-plan-execute ISS-001,ISS-002,ISS-003"

Interactive Selection

codex -p "@.codex/prompts/codex-issue-plan-execute"
# Then select issues from the list

Resume from Snapshot

codex -p "@.codex/prompts/codex-issue-plan-execute --resume snapshot-path"

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Skill Version: 1.0 Execution Mode: Autonomous Status: Ready for Customization