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todo-accelerator待办事项加速器

Agent Skill

todo-accelerator 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

4,110

周安装

173

GitHub Stars

公开资料未说明

下载量

1,439
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:todo-accelerator(待办事项加速器)
来源仓库:https://github.com/liusining/todo-accelerator
安装命令:
openclaw skills install todo-accelerator
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 todo-accelerator

简介

todo-accelerator 在代理心跳期间自动捕获待办事项,实现任务的无缝插入与管理。

  • 适合需要持续任务同步或被动提醒的场景,如开发迭代或日常事务监控。
  • 安装后无需显式调用,由系统事件触发,但需确保技能处于激活状态。
  • 使用前应检查事件监听权限,避免与其他技能冲突;注意隐私数据本地化处理。
  • 建议查看心跳频率设置,平衡响应速度与资源消耗。

SKILL.md

name
todo-accelerator
description
Use when a user needs to add a new task or record a pending to-do item; when prompting an Agent to execute a pending task; during Agent heartbeat events to pick up and work on tasks; when a user expresses interest in a topic for later research, saves a bookmark for processing, or asks for help preparing deliverables. Not for reminders (eating, sleeping, meetings).

To-Do Accelerator

Collaborative task management between users and AI Agents. Agents pick up tasks, work on them, deliver results, and update progress — functioning as teammates with the user. The Obsidian Kanban board serves as the shared communication channel.

Setup

Check: If todo-accelerator-config.yaml exists in the agent's workspace → ready to use. If not → follow initialization.md in this directory (one-time process).

Working Scenarios

ScenarioAgent Action
User describes a new task or bookmarks a topicAsk for missing details (targets, requirements, priority) → add-todo
Agent heartbeat eventCall work-on-todo → process the returned prompt → commit when done or blocked
User asks to handle a specific taskCall list-pending → confirm with user → work-on-todo --name "..."commit

Commands

Base command (referred to as <CMD> below):

python3 <skill-dir>/scripts/todo.py --config <workspace>/todo-accelerator-config.yaml

Replace <skill-dir> with the absolute path to this skill's directory, and <workspace> with the agent's workspace directory.

add-todo

Create a new to-do with a companion note, added under "Ideas".

<CMD> add-todo --name "title" [--targets "outcome1" "outcome2"] [--requirements "req1" "req2"] [--priority N] [--allow-subagent | --no-allow-subagent] [--assigned-agent "agent-id"]

Example:

<CMD> add-todo --name "Research AutoResearch" --targets "Summary of features and setup guide" --requirements "Read the README" "Try running the demo" "Write up findings" --priority 1

Do not guess parameters. If the user hasn't specified targets or requirements, ask them:

  • "What outcome do you expect from this?"
  • "Are there specific sub-tasks or questions to address?"
  • "Should this be prioritized? (0 = normal, higher = more urgent)"

work-on-todo

Pick up the highest-priority to-do from Ideas and prepare it for processing.

<CMD> work-on-todo
<CMD> work-on-todo --name "specific todo"

Example:

<CMD> work-on-todo --name "Research AutoResearch"

Behavior:

  • Without --name: auto-selects by priority (highest first, random among ties)
  • With --name: works on that specific to-do (confirm exact name with user first)
  • If the selected to-do has no unchecked requirements → moves it to 审阅中 and skips (no action needed)
  • Otherwise → moves card from Ideas to 推进中, increments iteration count, and returns a structured prompt

After work-on-todo returns, follow the instructions in references/processing-work-on-todo.md.

commit

Check off completed requirements and finalize the current round of work.

<CMD> commit --name "todo name" --completed "requirement 1" "requirement 2"

Example:

<CMD> commit --name "Research AutoResearch" --completed "Read the README" "Try running the demo"

Each --completed string must exactly match an unchecked requirement in the note's "What's More" section. If any string doesn't match, the script returns an error with the remaining unchecked requirements — re-examine and pass the exact strings.

The script moves the card to 审阅中 after committing.

list-pending

List all to-dos under "Ideas" with their priority levels.

<CMD> list-pending

Example:

<CMD> list-pending

Note Structure

Each to-do has a companion .md note. For YAML frontmatter properties, see references/note-yaml-properties.md.

SectionPurposeHow to update
What's MoreRequirements checklist (- [ ] / - [x])Managed via commit command
TargetFinal results and deliverablesWrite directly in the note
Investigation and ProblemsOngoing findings, progress notes, obstaclesWrite directly in the note

Case Studies

See references/case-study.md for detailed usage examples covering the full lifecycle.

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

71.94%
按下载量换算1,035

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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。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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