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multitaskmultitask 搜索

Agent Skill

multitask 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。

总安装

1,909

周安装

78

GitHub Stars

55

下载量

618
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

2

许可证

unknown

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:multitask(multitask 搜索)
来源仓库:https://github.com/rysweet/amplihack
仓库路径:skills/multitask
安装命令:
npx skills add https://github.com/rysweet/amplihack --skill multitask
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/rysweet/amplihack --skill multitask

简介

用于查找、检索和筛选相关信息,支持多维度关键词匹配。

  • 适合在复杂任务中快速定位所需资料或技术方案。
  • 可通过来源仓库进一步验证其搜索范围和准确性。
  • 安装命令:npx skills add https://github.com/rysweet/amplihack --skill multitask。
  • 注意评估是否触发外部 API 调用或数据导出功能。

SKILL.md

Multitask Skill

Purpose

Execute multiple independent development tasks in parallel. Each workstream runs in an isolated /tmp clone with its own Recipe Runner process following code-enforced workflow steps.

Key Advantage: Uses Recipe Runner YAML recipes instead of prompt-based markdown workflows. Python controls step execution, making it impossible to skip steps.

Quick Start

Inline Tasks

/multitask
- #123 (feat/add-auth): Implement user authentication
- #124 (feat/add-logging): Add structured logging
- #125 (feat/update-api): Update API endpoints

JSON Config

Create workstreams.json:

[
  {
    "issue": 123,
    "branch": "feat/add-auth",
    "description": "User authentication",
    "task": "Implement JWT-based authentication with login/logout endpoints",
    "recipe": "default-workflow"
  },
  {
    "issue": 124,
    "branch": "feat/add-logging",
    "description": "Structured logging",
    "task": "Add structured JSON logging across all API endpoints"
  }
]

Then: /multitask workstreams.json

How It Works

User provides task list
        |
        v
For each task:
  1. Clone branch to /tmp/amplihack-workstreams/ws-{issue}/
  2. Write launcher.py (Recipe Runner with CLISubprocessAdapter)
  3. Write run.sh (sets session tree vars, runs launcher.py)
  4. Launch subprocess via Popen
        |
        v
Monitor all workstreams (60s intervals)
        |
        v
Report: PR numbers, success/failure, runtime

Why Recipe Runner?

AspectClassic (markdown)Recipe Runner (YAML)
Step orderingPrompt-based (skippable)Code-enforced (Python loop)
Template variablesNone{{task_description}}, {{repo_path}}
Error handlingImplicitFail-fast per step
Progress trackingOpaqueStep-by-step status

Critical Implementation Details

  1. /tmp clones (not worktrees): Worktree symlinks confuse nested Claude sessions. Clean clones avoid this.
  2. --subprocess-safe: Classic mode passes this flag to skip staging/env updates, preventing concurrent write races on ~/.amplihack/.claude/ (issue #2567).
  3. Recipe Runner adapter: CLISubprocessAdapter shells out to claude -p for each agent step within the recipe (no amplihack wrapper, so no staging race).
  4. Child env cleanup: The shared build_child_env() utility strips blocking env vars and propagates session tree context.

Execution Modes

Recipe Mode (Default)

Each workstream runs run_recipe_by_name() through a Python launcher:

from amplihack.recipes import run_recipe_by_name

result = run_recipe_by_name("default-workflow",
    user_context={"task_description": task, "repo_path": "."})

Classic Mode

Falls back to single-session prompt-based execution with --subprocess-safe to avoid concurrent staging races (see issue #2567):

amplihack claude --subprocess-safe -- -p "@TASK.md Execute autonomously following DEFAULT_WORKFLOW.md."

The --subprocess-safe flag skips all staging/env updates so parallel workstreams don't race on ~/.amplihack/.claude/. The parent amplihack process has already staged the framework files.

Use --mode classic when Recipe Runner is unavailable or for tasks that benefit from full session context.

Available Recipes

Any recipe in amplifier-bundle/recipes/ can be used per-workstream:

RecipeStepsBest For
default-workflow52Features, bugs, refactoring (default)
investigation-workflow23Research, codebase analysis
verification-workflow5Trivial changes, config updates
auto-workflow9Autonomous iteration until complete

Specify per-task: "recipe": "investigation-workflow" in JSON config.

Monitoring

# Watch all logs
tail -f /tmp/amplihack-workstreams/log-*.txt

# Check specific workstream
tail -f /tmp/amplihack-workstreams/log-123.txt

# Check running processes
ps aux | grep launcher.py

# Final report
cat /tmp/amplihack-workstreams/REPORT.md

When to Read Supporting Files

NeedFile
Full API, config options, architecturereference.md
Real-world usage examplesexamples.md
Python orchestrator sourceorchestrator.py

Disk Management & Cleanup

Understanding Disk Usage

Each workstream creates a full git clone (~1.5GB). With 10 parallel workstreams, this is ~15GB of temporary disk usage.

Locations:

  • /tmp/amplihack-workstreams/ws-{issue}/ - Each workstream's working directory
  • /tmp/amplihack-workstreams/log-{issue}.txt - Log files (kept separately)
  • /tmp/amplihack-workstreams/REPORT.md - Final execution report

When to Clean Up

✅ SAFE to delete:

  • PR has been merged to main
  • You've finished debugging/inspecting the workstream
  • You need disk space for new workstreams
  • All PRs from a multitask session are complete

❌ NOT safe to delete:

  • PR is still under review
  • PR has merge conflicts you need to resolve manually
  • You might need to inspect the working directory for debugging
  • Workstream failed and you haven't diagnosed the issue

Manual Cleanup Commands

# Check disk usage first
du -sh /tmp/amplihack-workstreams/*

# Clean up specific workstream (after PR merged)
rm -rf /tmp/amplihack-workstreams/ws-123

# Clean up all workstreams (after all PRs merged)
rm -rf /tmp/amplihack-workstreams/ws-*

# Keep log files, delete only working directories
find /tmp/amplihack-workstreams -type d -name "ws-*" -exec rm -rf {} +

# Check available disk space
df -h /tmp

Automatic Cleanup (Helper Command)

After merging PRs, use the cleanup helper to automatically remove merged workstreams:

# Clean up all workstreams with merged PRs
python .claude/skills/multitask/orchestrator.py --cleanup workstreams.json

# Dry run (show what would be deleted)
python .claude/skills/multitask/orchestrator.py --cleanup --dry-run workstreams.json

The cleanup helper:

  • Checks each workstream's PR status using gh CLI
  • Only deletes workstreams with MERGED status
  • Preserves log files for historical reference
  • Reports disk space freed

Disk Space Monitoring

The orchestrator automatically checks disk space before launching workstreams:

⚠️  WARNING: Only 8.2GB free in /tmp
Each workstream requires ~1.5GB. Consider cleaning up:
  rm -rf /tmp/amplihack-workstreams/ws-*
Continue anyway? (y/N):

Rule of thumb: Keep at least 20GB free for comfortable multi-workstream development.

Preventing Disk Issues

  1. Before large multitask runs (10+ workstreams): df -h /tmp # Check available space rm -rf /tmp/amplihack-workstreams/ws-* # Clean old workstreams
  2. After merging PRs: python orchestrator.py --cleanup workstreams.json
  3. Monitor during execution: watch -n 60 'du -sh /tmp/amplihack-workstreams && df -h /tmp'

Troubleshooting

Empty log files: Process started but exited immediately. Check if amplihack package is importable in the clone's environment.

Recipe not found: Ensure amplifier-bundle/recipes/ exists in the cloned branch. The recipe discovery checks this directory first.

Fallback: If recipe mode fails, retry with --mode classic to use the prompt-based approach.

Disk full during execution: The orchestrator warns if <10GB free. If disk fills mid-execution, manually clean up: rm -rf /tmp/amplihack-workstreams/ws-* (after stopping running workstreams).

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

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

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

Codex

37.09%
按下载量换算229

Claude

26.44%
按下载量换算163

Cursor

20.4%
按下载量换算126

Gemini CLI

9.18%
按下载量换算57

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/rysweet/amplihack --skill multitask 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 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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