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task-extractor任务提取器

Agent Skill

task-extractor 用于查找、检索和筛选相关信息,适合在 OpenClaw 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

2,661

周安装

112

GitHub Stars

公开资料未说明

下载量

932
OpenClaw

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

MIT-0

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:task-extractor(任务提取器)
来源仓库:https://github.com/dodge1218/task-extractor
安装命令:
openclaw skills install task-extractor
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install task-extractor

简介

从用户消息中提取多任务项并完成状态跟踪工具。

  • 适用于混合提示转储与批量操作项目管理场景。
  • 支持超过三个可操作项目的识别与验证。task-extractor 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 安装前需确认权限范围、维护状态及是否持久化任务列表。
  • 建议结合原始 README 核验提取规则与去重逻辑。

SKILL.md

name
task-extractor
version
1.0.0
description
Extract, track, and verify completion of multiple tasks from a single user message. Use when any message contains 3+ actionable items, a prompt dump with mixed instructions, or a compound request. Prevents task drop by saving to TASK_QUEUE.md before executing. Reports completion status per item.

Task Extractor

Parse multi-task messages → numbered queue → execute sequentially → verify each → report.

Activation

Trigger on ANY user message containing 3+ distinct actionable items. Signs:

  • Multiple sentences starting with verbs ("build", "fix", "send", "check", "add", "research")
  • Comma-separated or period-separated instructions
  • Mixed topics in one paragraph
  • "also", "and then", "plus", "oh and", "one more thing"

If uncertain whether to activate: activate. False positives (structuring a 2-item request) cost nothing. False negatives (dropping task #7 of 12) cost trust.

Step 1: EXTRACT (before any execution)

Parse the message into individual tasks. Each task gets:

  • Number (sequential)
  • Summary (one line, imperative verb)
  • Type: BUILD | FIX | RESEARCH | SEND | DEPLOY | CONFIG | OTHER
  • Estimated effort: QUICK (< 5 min) | MEDIUM (5-30 min) | HEAVY (30+ min / sub-agent)

Write to workspace/TASK_QUEUE.md:

# TASK_QUEUE — [date] [time]
# Source: [channel]
# Total: [N]
# Status: IN PROGRESS

| # | Task | Type | Effort | Status | Artifact |
|---|------|------|--------|--------|----------|
| 1 | [summary] | BUILD | HEAVY | ⏳ | |
| 2 | [summary] | FIX | QUICK | ⏳ | |
| 3 | [summary] | SEND | QUICK | ⏳ | |
...

Step 2: RECEIPT

Reply to the user with the extracted checklist BEFORE starting work:

📋 Extracted [N] tasks from your message:

1. ⏳ [task summary]
2. ⏳ [task summary]
3. ⏳ [task summary]
...

Starting now. I'll check each off as I go.

Do NOT ask "is this right?" unless genuinely ambiguous. Convert ambiguity into a task and execute. Ryan's rule: don't interrogate, just do.

Step 3: EXECUTE

Work through tasks in dependency order (not necessarily numerical order):

  • Independent QUICK tasks first (batch them in parallel tool calls)
  • MEDIUM tasks next
  • HEAVY tasks: spawn sub-agents with clear scope

For each completed task, update TASK_QUEUE.md:

  • (done) or (failed) or ⚠️ (partial) or 🔄 (spawned sub-agent)
  • Fill in the Artifact column (file path, URL, commit hash, or "n/a")

Step 4: RECONCILE

After all tasks are attempted (or sub-agents spawned), reply with the final checklist:

📋 Task Report ([completed]/[total]):

1. ✅ [task] → [artifact]
2. ✅ [task] → [artifact]
3. 🔄 [task] → sub-agent running, will announce when done
4. ❌ [task] → [reason for failure]
5. ⚠️ [task] → [what was done, what's left]

Step 5: VERIFY (on sub-agent completion)

When a sub-agent announces completion:

  • Update TASK_QUEUE.md
  • If ALL tasks are now ✅/❌, send final summary
  • If tasks remain ⏳, continue working

Rules

  1. NEVER skip the extract step. Even if the answer seems obvious. The extract step IS the safety net.
  2. NEVER mark a task ✅ without evidence. Evidence = file exists, command succeeded, API returned 200, deploy URL works.
  3. If a task fails, say WHY. Not just ❌ — include the error, the blocker, or what's needed.
  4. Sub-agent tasks get 🔄 until completion event arrives. Don't mark them ✅ optimistically.
  5. TASK_QUEUE.md is the source of truth. If context overflows, re-read it. If a session restarts, re-read it.
  6. One TASK_QUEUE at a time. If a new multi-task message arrives while one is active, append to the existing queue (renumber).
  7. Checkpoint at 5 completed tasks. Update the user with progress so far.

Edge Cases

"Do X and also Y but wait on Z"

  • X and Y get ⏳, Z gets 🕐 (blocked — note the dependency)

Sub-agent timeout

  • Mark as ⚠️, note what was attempted, offer to retry or take over manually

User changes mind mid-execution

  • Update TASK_QUEUE.md, cross out cancelled tasks with ~~strikethrough~~, continue with remaining

Overlapping tasks

  • If task 3 and task 7 are really the same thing, merge them. Note in Artifact: "merged with #3"

Anti-patterns

  • ❌ Reading the message, immediately jumping into task #1 without extracting all tasks
  • ❌ Marking a sub-agent task ✅ before the completion event
  • ❌ Saying "I'll get to that" and then forgetting
  • ❌ Only reporting on the tasks you completed, silently dropping the ones you didn't
  • ❌ Asking "which one should I do first?" — just prioritize by dependency + effort and go

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

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

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

OpenClaw

93.07%
按下载量换算867

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

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 openclaw skills install task-extractor 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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