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Agent Skill · 研究检索

parallel-dev-cycle(并行开发周期)

parallel-dev-cycle 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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。

parallel-dev-cycle 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为执行命令;许可证为 MIT,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 39,223。

总安装 1,444周安装 59GitHub Stars 1,874下载 463核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT

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:parallel-dev-cycle(并行开发周期)
来源仓库:https://github.com/catlog22/claude-code-workflow
仓库路径:skills/parallel-dev-cycle
安装命令:
npx skills add https://github.com/catlog22/claude-code-workflow --skill parallel-dev-cycle
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/catlog22/claude-code-workflow --skill parallel-dev-cycle

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于查找、检索和筛选相关信息,支持基于关键词或任务场景快速定位候选结果。适用于需要信息收集、线索追踪或研究支持的场景,帮助 Agent 高效获取目标内容。通过 npx skills add 命令从指定仓库安装,建议结合原始 README 核验具体用法。

使用前需确认权限范围、维护状态,并评估是否涉及联网、命令执行或文件读写操作。parallel-dev-cycle 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/parallel-dev-cycle

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/catlog22/claude-code-workflow --skill parallel…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要执行命令,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

parallel-dev-cycle 怎么安装?

在终端执行 npx skills add https://github.com/catlog22/claude-code-workflow --skill parallel-dev-cycle。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

parallel-dev-cycle 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

parallel-dev-cycle 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 npx skills add https://github.com/catlog22/claude-code-workflow --skill parallel-dev-cycle;npx skills add catlog22/claude-code-workflow --skill "parallel-dev-cycle" 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

parallel-dev-cycle 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

parallel-dev-cycle 用的人多吗?

公开数据是累计安装 1,444 次,近一周安装 59 次,下载 463 次,GitHub 1,874 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

parallel-dev-cycle 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。
  • 来源仓库有 1,874 星,维护活跃度相对可查。

先想清楚的地方

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 不能接受 Skill 在你机器上执行命令的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
parallel-dev-cycle

并行开发周期 · 本页

1,4441,874执行命令MIT有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Parallel Dev Cycle

Multi-agent parallel development cycle using Codex subagent pattern with four specialized workers:

  1. Requirements Analysis & Extension (RA) - Requirement analysis and self-enhancement
  2. Exploration & Planning (EP) - Codebase exploration and implementation planning
  3. Code Development (CD) - Code development with debug strategy support
  4. Validation & Archival Summary (VAS) - Validation and archival summary

Orchestration logic (phase management, state updates, feedback coordination) runs inline in the main flow — no separate orchestrator agent is spawned. Only 4 worker agents are allocated.

Each agent maintains one main document (e.g., requirements.md, plan.json, implementation.md) that is completely rewritten per iteration, plus auxiliary logs (changes.log, debug-log.ndjson) that are append-only.

Architecture Overview

┌─────────────────────────────────────────────────────────────┐
│                    User Input (Task)                        │
└────────────────────────────┬────────────────────────────────┘
                             │
                             v
              ┌──────────────────────────────┐
              │  Main Flow (Inline Orchestration)  │
              │  Phase 1 → 2 → 3 → 4              │
              └──────────────────────────────┘
                             │
        ┌────────────────────┼────────────────────┐
        │                    │                    │
        v                    v                    v
    ┌────────┐         ┌────────┐         ┌────────┐
    │  RA    │         │  EP    │         │  CD    │
    │Agent   │         │Agent   │         │Agent   │
    └────────┘         └────────┘         └────────┘
        │                    │                    │
        └────────────────────┼────────────────────┘
                             │
                             v
                         ┌────────┐
                         │  VAS   │
                         │ Agent  │
                         └────────┘
                             │
                             v
              ┌──────────────────────────────┐
              │    Summary Report            │
              │  & Markdown Docs             │
              └──────────────────────────────┘

Key Design Principles

  1. Main Document + Auxiliary Logs: Each agent maintains one main document (rewritten per iteration) and auxiliary logs (append-only)
  2. Version-Based Overwrite: Main documents completely rewritten per version; logs append-only
  3. Automatic Archival: Old main document versions automatically archived to history/ directory
  4. Complete Audit Trail: Changes.log (NDJSON) preserves all change history
  5. Parallel Coordination: Four agents launched simultaneously; coordination via shared state and inline main flow
  6. File References: Use short file paths instead of content passing
  7. Self-Enhancement: RA agent proactively extends requirements based on context
  8. Shared Discovery Board: All agents share exploration findings via discoveries.ndjson — read on start, write as you discover, eliminating redundant codebase exploration

Arguments

ArgRequiredDescription
TASKOne of TASK or --cycle-idTask description (for new cycle, mutually exclusive with --cycle-id)
--cycle-idOne of TASK or --cycle-idExisting cycle ID to continue (from API or previous session)
--extendNoExtension description (only valid with --cycle-id)
--autoNoAuto-cycle mode (run all phases sequentially without user confirmation)
--parallelNoNumber of parallel agents (default: 4, max: 4)

Auto Mode

When --auto: Run all phases sequentially without user confirmation between iterations. Use recommended defaults for all decisions. Automatically continue iteration loop until tests pass or max iterations reached.

Prep Package Integration

When prep-package.json exists at {projectRoot}/.workflow/.cycle/prep-package.json, Phase 1 consumes it to:

  • Use refined task description instead of raw TASK
  • Apply auto-iteration config (convergence criteria, phase gates)
  • Inject per-iteration agent focus directives (0→1 vs 1→100)

Prep packages are generated by the interactive prompt /prompts:prep-cycle. See phases/00-prep-checklist.md for schema.

Execution Flow

Input Parsing:
   └─ Parse arguments (TASK | --cycle-id + --extend)
   └─ Convert to structured context (cycleId, state, progressDir)
   └─ Initialize progress tracking: functions.update_plan([...phases])

Phase 1: Session Initialization
   └─ Ref: phases/01-session-init.md
      ├─ Create new cycle OR resume existing cycle
      ├─ Initialize state file and directory structure
      └─ Output: cycleId, state, progressDir

Phase 2: Agent Execution (Parallel)
   └─ Ref: phases/02-agent-execution.md
      ├─ Tasks attached: Spawn RA → Spawn EP → Spawn CD → Spawn VAS → Wait all
      ├─ Spawn RA, EP, CD, VAS agents in parallel
      ├─ Wait for all agents with timeout handling
      └─ Output: agentOutputs (4 agent results)

Phase 3: Result Aggregation & Iteration
   └─ Ref: phases/03-result-aggregation.md
      ├─ Parse PHASE_RESULT from each agent
      ├─ Detect issues (test failures, blockers)
      ├─ Decision: Issues found AND iteration < max?
      │   ├─ Yes → Send feedback via assign_task, loop back to Phase 2
      │   └─ No → Proceed to Phase 4
      └─ Output: parsedResults, iteration status

Phase 4: Completion & Summary
   └─ Ref: phases/04-completion-summary.md
      ├─ Generate unified summary report
      ├─ Update final state
      ├─ Sync session state: $session-sync -y "Dev cycle complete: {iterations} iterations"
      ├─ Close all agents
      └─ Output: final cycle report with continuation instructions

Phase Reference Documents (read on-demand when phase executes):

PhaseDocumentPurpose
1phases/01-session-init.mdSession creation/resume and state initialization
2phases/02-agent-execution.mdParallel agent spawning and execution
3phases/03-result-aggregation.mdResult parsing, feedback generation, iteration handling
4phases/04-completion-summary.mdFinal summary generation and cleanup

Data Flow

User Input (TASK | --cycle-id + --extend)
    ↓
[Parse Arguments]
    ↓ cycleId, state, progressDir

Phase 1: Session Initialization
    ↓ cycleId, state, progressDir (initialized/resumed)

Phase 2: Agent Execution
    ├─ All agents read coordination/discoveries.ndjson on start
    ├─ Each agent explores → writes new discoveries to board
    ├─ Later-finishing agents benefit from earlier agents' findings
    ↓ agentOutputs {ra, ep, cd, vas} + shared discoveries.ndjson

Phase 3: Result Aggregation
    ↓ parsedResults, hasIssues, iteration count
    ↓ [Loop back to Phase 2 if issues and iteration < max]
    ↓ (discoveries.ndjson carries over across iterations)

Phase 4: Completion & Summary
    ↓ finalState, summaryReport

Return: cycle_id, iterations, final_state

Session Structure

{projectRoot}/.workflow/.cycle/
├── {cycleId}.json                                 # Master state file
├── {cycleId}.progress/
    ├── ra/
    │   ├── requirements.md                        # Current version (complete rewrite)
    │   ├── changes.log                            # NDJSON complete history (append-only)
    │   └── history/                               # Archived snapshots
    ├── ep/
    │   ├── exploration.md                         # Codebase exploration report
    │   ├── architecture.md                        # Architecture design
    │   ├── plan.json                              # Structured task list (current version)
    │   ├── changes.log                            # NDJSON complete history
    │   └── history/
    ├── cd/
    │   ├── implementation.md                      # Current version
    │   ├── debug-log.ndjson                       # Debug hypothesis tracking
    │   ├── changes.log                            # NDJSON complete history
    │   └── history/
    ├── vas/
    │   ├── summary.md                             # Current version
    │   ├── changes.log                            # NDJSON complete history
    │   └── history/
    └── coordination/
        ├── discoveries.ndjson                     # Shared discovery board (all agents append)
        ├── timeline.md                            # Execution timeline
        └── decisions.log                          # Decision log

State Management

Master state file: {projectRoot}/.workflow/.cycle/{cycleId}.json

{
  "cycle_id": "cycle-v1-20260122T100000-abc123",
  "title": "Task title",
  "description": "Full task description",
  "status": "created | running | paused | completed | failed",
  "created_at": "ISO8601", "updated_at": "ISO8601",
  "max_iterations": 5, "current_iteration": 0,
  "agents": {
    "ra":  { "status": "idle | running | completed | failed", "output_files": [] },
    "ep":  { "status": "idle", "output_files": [] },
    "cd":  { "status": "idle", "output_files": [] },
    "vas": { "status": "idle", "output_files": [] }
  },
  "current_phase": "init | ra | ep | cd | vas | aggregation | complete",
  "completed_phases": [],
  "requirements": null, "plan": null, "changes": [], "test_results": null,
  "coordination": { "feedback_log": [], "blockers": [] }
}

Recovery: If state corrupted, rebuild from .progress/ markdown files and changes.log.

Progress Tracking

Initialization (MANDATORY)

// Initialize progress tracking after input parsing
functions.update_plan([
  { id: "phase-1", title: "Phase 1: Session Initialization", status: "in_progress" },
  { id: "phase-2", title: "Phase 2: Agent Execution", status: "pending" },
  { id: "phase-3", title: "Phase 3: Result Aggregation", status: "pending" },
  { id: "phase-4", title: "Phase 4: Completion & Summary", status: "pending" }
])

Phase Transitions

// After Phase 1 completes
functions.update_plan([
  { id: "phase-1", status: "completed" },
  { id: "phase-2", status: "in_progress" }
])

// After Phase 2 completes
functions.update_plan([
  { id: "phase-2", status: "completed" },
  { id: "phase-3", status: "in_progress" }
])

// After Phase 3 — iterate or complete
// If iterating back to Phase 2:
functions.update_plan([
  { id: "phase-3", status: "completed" },
  { id: "phase-2", title: "Phase 2: Agent Execution (Iteration N)", status: "in_progress" }
])
// If proceeding to Phase 4:
functions.update_plan([
  { id: "phase-3", status: "completed" },
  { id: "phase-4", status: "in_progress" }
])

// After Phase 4 completes
functions.update_plan([{ id: "phase-4", status: "completed" }])

Versioning

  • 1.0.0: Initial cycle → 1.x.0: Each iteration (minor bump)
  • Each iteration: archive old → complete rewrite → append changes.log
Archive: copy requirements.md → history/requirements-v1.0.0.md
Rewrite: overwrite requirements.md with v1.1.0 (complete new content)
Append:  changes.log ← {"timestamp","version":"1.1.0","action":"update","description":"..."}
Agent OutputRewrite (per iteration)Append-only
RArequirements.mdchanges.log
EPexploration.md, architecture.md, plan.jsonchanges.log
CDimplementation.md, issues.mdchanges.log, debug-log.ndjson
VASsummary.md, test-results.jsonchanges.log

Coordination Protocol

Execution Order: RA → EP → CD → VAS (dependency chain, all spawned in parallel but block on dependencies)

Shared Discovery Board

All agents share a real-time discovery board at coordination/discoveries.ndjson. Each agent reads it on start and appends findings during work. This eliminates redundant codebase exploration.

Lifecycle:

  • Created by the first agent to write a discovery (file may not exist initially)
  • Carries over across iterations — never cleared or recreated
  • Agents use Bash echo '...' >> discoveries.ndjson to append entries

Format: NDJSON, each line is a self-contained JSON with required top-level fields ts, agent, type, data:

{"ts":"2026-01-22T10:00:00+08:00","agent":"ra","type":"tech_stack","data":{"language":"TypeScript","framework":"Express","test":"Jest","build":"tsup"}}

Discovery Types:

typeDedup KeyWritersReadersRequired data Fields
tech_stacksingletonRAEP, CD, VASlanguage, framework, test, build
project_configdata.pathRAEP, CDpath, key_deps[], scripts{}
existing_featuredata.nameRA, EPCDname, files[], summary
architecturesingletonEPCD, VASpattern, layers[], entry
code_patterndata.nameEP, CDCD, VASname, description, example_file
integration_pointdata.fileEPCDfile, description, exports[]
similar_impldata.featureEPCDfeature, files[], relevance
code_conventionsingletonCDVASnaming, imports, formatting
utilitydata.nameCDVASname, file, usage
test_commandsingletonCD, VASVAS, CDunit, integration(opt), coverage(opt)
test_baselinesingletonVASCDtotal, passing, coverage_pct, framework, config
test_patternsingletonVASCDstyle, naming, fixtures
blockerdata.issueanyallissue, severity, impact

Protocol Rules:

  1. Read board before own exploration → skip covered areas (if file doesn't exist, skip)
  2. Write discoveries immediately via Bash echo >> → don't batch
  3. Deduplicate — check existing entries; skip if same type + dedup key value already exists
  4. Append-only — never modify or delete existing lines

Agent → Main Flow Communication

PHASE_RESULT:
- phase: ra | ep | cd | vas
- status: success | failed | partial
- files_written: [list]
- summary: one-line summary
- issues: []

Main Flow → Agent Communication

Feedback via assign_task (file refs + issue summary, never full content):

## FEEDBACK FROM [Source]
[Issue summary with file:line references]
## Reference
- File: .progress/vas/test-results.json (v1.0.0)
## Actions Required
1. [Specific fix]

Rules: Only main flow writes state file. Agents read state, write to own .progress/{agent}/ directory only.

Core Rules

  1. Start Immediately: First action is functions.update_plan initialization, then Phase 1 execution
  2. Progressive Phase Loading: Read phase docs ONLY when that phase is about to execute
  3. Parse Every Output: Extract PHASE_RESULT data from each agent for next phase
  4. Auto-Continue: After each phase, execute next pending phase automatically
  5. Track Progress: Update functions.update_plan at each phase transition
  6. Single Writer: Only main flow writes to master state file; agents report via PHASE_RESULT
  7. File References: Pass file paths between agents, not content
  8. DO NOT STOP: Continuous execution until all phases complete or max iterations reached

Error Handling

Error TypeRecovery
Agent timeoutassign_task requesting convergence, then retry
State corruptedRebuild from progress markdown files and changes.log
Agent failedRe-spawn agent with previous context
Conflicting resultsMain flow sends reconciliation request
Missing filesRA/EP agents identify and request clarification
Max iterations reachedGenerate summary with remaining issues documented

Coordinator Checklist (Main Flow)

Before Each Phase

  • Read phase reference document
  • Check current state for dependencies
  • Update functions.update_plan with phase status

After Each Phase

  • Parse agent outputs (PHASE_RESULT)
  • Update master state file
  • Update functions.update_plan phase completion
  • Determine next action (continue / iterate / complete)

Reference Documents

DocumentPurpose
roles/Agent role definitions (RA, EP, CD, VAS)

Usage

# Start new cycle
/parallel-dev-cycle TASK="Implement real-time notifications"

# Continue cycle
/parallel-dev-cycle --cycle-id=cycle-v1-20260122-abc123

# Iteration with extension
/parallel-dev-cycle --cycle-id=cycle-v1-20260122-abc123 --extend="Also add email notifications"

# Auto mode
/parallel-dev-cycle --auto TASK="Add OAuth authentication"

平台分布

Claude Code

29.59%
按下载量换算137

windsurf

26.16%
按下载量换算121

OpenCode

17.07%
按下载量换算79

Cursor

13.49%
按下载量换算62

Codex

8.56%
按下载量换算40

Antigravity

3.76%
按下载量换算17

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/catlog22/claude-code-workflow --skill parallel-dev-cycle;npx skills add catlog22/claude-code-workflow --skill "parallel-dev-cycle" 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。

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