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Agent Skill · 研究检索

parallel-execution(并行执行)

parallel-execution 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-execution 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;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 67,168。

总安装 250周安装 10GitHub Stars 公开资料未说明下载 81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
unknown

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-execution(并行执行)
来源仓库:https://github.com/squirrel289/pax
仓库路径:skills/parallel-execution
安装命令:
npx skills add https://github.com/squirrel289/pax --skill parallel-execution
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。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/squirrel289/pax --skill parallel-execution

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。

parallel-execution 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。它支持通过指定仓库、路径或关键词进行信息聚合与过滤,适用于研究、数据整理等场景。

可通过 npx skills add 命令从 GitHub 安装,具体用法需结合原始 README 进一步确认。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。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/parallel-execution

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/squirrel289/pax --skill parallel-execution;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-execution 怎么安装?

在终端执行 npx skills add https://github.com/squirrel289/pax --skill parallel-execution。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

parallel-execution 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-execution 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/squirrel289/pax --skill parallel-execution 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-execution 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

parallel-execution 用的人多吗?

公开数据是累计安装 250 次,近一周安装 10 次,下载 81 次。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-execution 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

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。
  • 第三方扫描已通过,常见的高风险行为没有命中。

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。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 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。
  • 需要明确授权才能用到公司项目里的场景。
  • 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-execution

并行执行 · 本页

250—执行命令未明确通过

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 Execution

CRITICAL: This skill teaches how to execute multiple tasks simultaneously for maximum efficiency.

The Fundamental Rule

ALL runSubagent calls MUST be in a SINGLE function_calls block for true parallelism.

If runSubagent calls are in separate messages, they run SEQUENTIALLY, not in parallel.


Why Parallel Execution Matters

Sequential (SLOW - AVOID)

Message 1: Start Task A
           ↓ wait for completion
Message 2: Start Task B
           ↓ wait for completion
Message 3: Start Task C
           ↓ wait for completion

Total time = A + B + C = 90 seconds (if each takes 30s)

Parallel (FAST - USE THIS)

Message 1: Start Task A ─┐
           Start Task B ─┼─ All run simultaneously
           Start Task C ─┘

Total time ≈ max(A, B, C) = 30 seconds

Speedup: 3x faster with 3 parallel tasks


How to Execute in Parallel

Step 1: Identify Independent Tasks

Tasks are independent when:

  • They don't depend on each other's output
  • They don't modify the same files
  • They can run in any order

Step 2: Launch ALL Tasks in ONE Message

Launch all runSubagent calls in a single function_calls block:

<!-- CORRECT: All tasks in single function_calls block = PARALLEL -->
<function_calls>
<invoke name="runSubagent">
<parameter name="description">Analyze authentication module</parameter>
<parameter name="prompt">Review src/auth for security patterns...</parameter>
</invoke>
<invoke name="runSubagent">
<parameter name="description">Analyze API layer</parameter>
<parameter name="prompt">Review src/api for REST best practices...</parameter>
</invoke>
<invoke name="runSubagent">
<parameter name="description">Analyze database layer</parameter>
<parameter name="prompt">Review src/db for query optimization...</parameter>
</invoke>
</function_calls>

Step 3: Collect and Synthesize Results

After all tasks complete, combine their findings into a unified response.


Parallelization Patterns

Pattern 1: Task-Based Parallelization

When you have N independent tasks, spawn N subagents:

Implementation Plan:

1. Implement auth module
2. Create API endpoints
3. Add database schema
4. Write unit tests
5. Update documentation

Launch 5 parallel subagents:
├─ Subagent 1: Implement auth module
├─ Subagent 2: Create API endpoints
├─ Subagent 3: Add database schema
├─ Subagent 4: Write unit tests
└─ Subagent 5: Update documentation

All 5 in ONE message!

Pattern 2: Directory-Based Parallelization

Analyze different directories simultaneously:

Codebase Structure:
├── src/auth/
├── src/api/
├── src/db/
└── src/ui/

Launch 4 parallel subagents:
├─ Subagent 1: Analyze src/auth
├─ Subagent 2: Analyze src/api
├─ Subagent 3: Analyze src/db
└─ Subagent 4: Analyze src/ui

Pattern 3: Perspective-Based Parallelization

Review from multiple angles at once:

Code Review Perspectives:

- Security vulnerabilities
- Performance bottlenecks
- Test coverage gaps
- Architecture patterns

Launch 4 parallel subagents:
├─ Subagent 1: Security review
├─ Subagent 2: Performance analysis
├─ Subagent 3: Test coverage review
└─ Subagent 4: Architecture assessment

Pattern 4: Adversarial Verification

Use conflicting mandates for thorough review:

Verification Subagents (all parallel):
├─ Syntax & Type Checker
├─ Test Runner
├─ Lint & Style Checker
├─ Security Scanner
└─ Build Validator

Then (sequential, after above complete):
├─ False Positive Filter
├─ Missing Issues Finder
└─ Context Validator

TodoList Integration

When using parallel execution, mark ALL parallel tasks as in_progress simultaneously:

Before Launching Parallel Tasks

{
  "todos": [
    {
      "content": "Analyze auth module",
      "status": "in_progress",
      "activeForm": "Analyzing auth module"
    },
    {
      "content": "Analyze API layer",
      "status": "in_progress",
      "activeForm": "Analyzing API layer"
    },
    {
      "content": "Analyze database layer",
      "status": "in_progress",
      "activeForm": "Analyzing database layer"
    },
    {
      "content": "Synthesize findings",
      "status": "pending",
      "activeForm": "Synthesizing findings"
    }
  ]
}

After Each Task Completes

Mark as completed as results come in:

{
  "todos": [
    {
      "content": "Analyze auth module",
      "status": "completed",
      "activeForm": "Analyzing auth module"
    },
    {
      "content": "Analyze API layer",
      "status": "completed",
      "activeForm": "Analyzing API layer"
    },
    {
      "content": "Analyze database layer",
      "status": "in_progress",
      "activeForm": "Analyzing database layer"
    },
    {
      "content": "Synthesize findings",
      "status": "pending",
      "activeForm": "Synthesizing findings"
    }
  ]
}

When to Parallelize

Good Candidates

ScenarioParallel Approach
Multiple independent analysesOne subagent per analysis
Multi-file processingOne subagent per file/directory
Different review perspectivesOne subagent per perspective
Multiple independent featuresOne subagent per feature
Exploratory researchMultiple search strategies

When NOT to Parallelize

ScenarioWhy Sequential
Tasks with dependenciesB needs A's output
Same file modificationsRisk of conflicts
Sequential workflowsOrder matters (commit → push → PR)
Shared stateRace conditions
Limited resourcesOverwhelming the system

Performance Impact

# Parallel TasksSequential TimeParallel TimeSpeedup
260s30s2x
390s30s3x
5150s30s5x
10300s30s10x

Assuming each task takes ~30 seconds


Common Mistakes

Mistake 1: Separate Messages

WRONG (Sequential):
Message 1: "I'll start analyzing the auth module..."
<invoke name="runSubagent">Analyze auth</invoke>
Message 2: "Now let me analyze the API..."
<invoke name="runSubagent">Analyze API</invoke>

RIGHT (Parallel):
Message 1: "I'll analyze all modules in parallel..."
<function_calls>
<invoke name="runSubagent">Analyze auth</invoke>
<invoke name="runSubagent">Analyze API</invoke>
<invoke name="runSubagent">Analyze DB</invoke>
</function_calls>

Mistake 2: Announcing Before Acting

WRONG:
"I'm going to launch three parallel tasks to analyze the codebase."
[waits for response]
"Now launching the tasks..."

RIGHT:
"Launching three parallel analysis tasks now:"
<function_calls>
<invoke name="runSubagent">...</invoke>
<invoke name="runSubagent">...</invoke>
<invoke name="runSubagent">...</invoke>
</function_calls>

Mistake 3: Forgetting Synthesis

WRONG:
Just dump all task outputs without integration

RIGHT:
After receiving all results, synthesize:

- Identify common themes
- Resolve contradictions
- Prioritize findings
- Create unified recommendations

Parallel Execution Checklist

Before launching parallel tasks, verify:

  • Tasks are truly independent
  • No shared file modifications
  • No sequential dependencies
  • All tasks in SINGLE function_calls block
  • TodoList updated with all in_progress
  • Synthesis step planned

Template: Parallel Analysis

## Launching Parallel Analysis

I'm analyzing this codebase from multiple perspectives simultaneously.

### Parallel Tasks

<function_calls>
<invoke name="runSubagent">
<parameter name="description">Security Review</parameter>
<parameter name="prompt">Analyze for security vulnerabilities, focusing on:

- Authentication/authorization
- Input validation
- Secrets handling</parameter>
  </invoke>

<invoke name="runSubagent">
<parameter name="description">Performance Review</parameter>
<parameter name="prompt">Analyze for performance issues, focusing on:
- N+1 queries
- Memory leaks
- Blocking operations</parameter>
</invoke>

<invoke name="runSubagent">
<parameter name="description">Test Coverage Review</parameter>
<parameter name="prompt">Analyze test coverage, focusing on:
- Missing test cases
- Edge cases
- Integration tests</parameter>
</invoke>
</function_calls>

### Synthesis (after all complete)

[Combine findings into prioritized report]

Quick Reference

RULE #1:
ALL runSubagent calls in SINGLE function_calls block = PARALLEL
runSubagent calls in SEPARATE messages = SEQUENTIAL

PATTERNS:
Task-based: One subagent per task
Directory-based: One subagent per directory
Perspective-based: One subagent per viewpoint
Adversarial: Multiple competing reviewers

TODOLIST:
Mark ALL parallel tasks as in_progress BEFORE launching
Mark each as completed AFTER receiving results

SPEEDUP:
N parallel tasks ≈ Nx faster
(5 tasks @ 30s each: 150s → 30s)

CHECKLIST:
☐ Tasks independent?
☐ No shared files?
☐ No dependencies?
☐ All in ONE function_calls block?
☐ Synthesis planned?

平台分布

Codex

33.31%
按下载量换算27

Claude

30.29%
按下载量换算25

Cursor

18.17%
按下载量换算15

Gemini CLI

10.09%
按下载量换算8

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

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/squirrel289/pax --skill parallel-execution 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。目前只有一个公开来源,建议同时核对源仓库。

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