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deep-planner深度规划师

Agent Skill

deep-planner 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

3,378

周安装

138

GitHub Stars

1

下载量

1,093
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:deep-planner(深度规划师)
来源仓库:https://github.com/jzw6/deep-planner
安装命令:
openclaw skills install deep-planner
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 deep-planner

简介

深度规划师用于复杂任务的结构化拆解与执行路径设计。

  • 适合多步骤项目、研究计划或需分阶段完成的场景。
  • 通过内置工作流自动生成子目标并分配执行顺序。deep-planner 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 依赖宿主环境配置,建议检查网络访问与文件读写权限。
  • 使用前请核实其是否兼容当前 OpenClaw 版本。

SKILL.md

name
deep-planner
description
|

Deep Planner

A planning, execution, and self-reflection protocol for complex agent tasks.

How It Works

The TodoList exists in two places simultaneously:

  • In the reply — visible to the user, updated as steps complete
  • In .todolist/ — persisted to disk, recoverable if context is truncated

Both stay in sync. The file is the backup; the conversation is the live view.


Execution Protocol

Step 0 — Resume or Start Fresh

Before anything else, check for interrupted tasks:

Scan .todolist/ for any file with status: in-progress
  Found → Read it, show the user the current state, ask: continue or start new?
  Not found → Proceed to Step 1

Step 1 — Parse the Request (internal, not shown to user)

Before generating a plan, resolve the following internally:

□ What is the core goal? (one sentence)
□ What is the final deliverable? (report / code / content / action sequence / ...)
□ What tools or skills are needed? (web search / browser / code execution / ...)
□ Are there any ambiguities that would lead to completely different execution paths?
    Yes → Ask the user first, then generate the TodoList
    No  → Make reasonable assumptions; document them in the plan's Assumptions block

Only stop to ask about blockers — not details you can reasonably infer. Consolidate all questions into a single message. Do not ask one at a time.


Step 2 — Generate the TodoList

Once the request is clear, output the plan and write it to disk simultaneously.

Format shown in the reply:

## 📋 Task Plan: {short task name}

**Goal:** {one-line description of the final deliverable}
**Steps:** {N}

---

- [ ] 1. {step description} `{tool or skill}`
- [ ] 2. {step description} `{tool or skill}`
- [ ] 3. {step description} `internal reasoning`
- [ ] ...

> 💡 Assumptions: {any assumptions made without user confirmation}

---
Starting step 1 →

Write to disk at .todolist/YYYYMMDD-{task-name}.md using the file format below.


Step 3 — Execute Step by Step

Work through the TodoList in order. After each step completes:

  1. Open the next reply with a status update — mark the step [x]
  2. Briefly describe what was produced (1–2 sentences)
  3. Update the file to reflect the new state
  4. Proceed to the next step

Reply header format (concise):

✅ Step 2 done → Starting step 3...

Pause and ask the user when:

  • A step is marked ❓ (critical information is missing)
  • Reality diverges significantly from the plan and replanning is needed
  • A tool call fails and there are multiple recovery paths to choose from

Step 4 — Wrap Up

When all steps are done:

  1. Show the fully checked-off TodoList in the reply
  2. Run the post-completion reflection check (see below)
  3. Update the file: set status: completed — leave the file in place, do not delete

Confidence Levels

Only annotate when uncertain. Do not label every step.

MarkMeaningAction
(default)Confident, proceedExecute directly
⚠️May involve inference or outdated infoExecute, flag uncertainty in output
Critical info missingPause, ask the user, then continue

Post-Completion Reflection

Run internally after all steps finish. Only surface issues that actually exist.

□ Was the core goal achieved?
□ Did I state anything I believed but didn't verify?  → Flag it
□ Are there ⚠️ steps whose conclusions need a caveat?
□ Is the deliverable complete with nothing skipped?

If issues exist, append to the final reply:

> ⚠️ Note: {X} is based on inference — consider verifying {specific thing}.

Anti-Hallucination Rules

These constraints are non-negotiable:

  1. No fabricated data — statistics, market figures, and research findings must have a source, or be explicitly labeled as estimates
  2. No fabricated citations — do not reference papers, reports, or news articles that may not exist
  3. Flag time-sensitive claims — anything described as "latest", "current", or "now" must note the knowledge cutoff date or recommend the user verify with a live search
  4. Be honest about limits — if a task is out of scope, say so clearly rather than producing low-confidence output

File Format

Path: .todolist/YYYYMMDD-{task-name}.md

# {Task Name}
Created: YYYY-MM-DD HH:MM
Status: in-progress | completed

## Goal
{One-line description of the final deliverable}

## TodoList
- [x] 1. {completed step}
- [x] 2. {completed step}
- [ ] 3. {current step} ← current
- [ ] 4. {upcoming step}

## Assumptions & Confirmations
- Assumed: {things inferred without user confirmation}
- Confirmed: {things the user explicitly answered}

## Progress
{done}/{total} steps completed

Task Type Templates

For common task types, load the matching template from the reference file:

Task TypeReference
Research & analysisreferences/task-types.md#research
Content creation (articles, posts)references/task-types.md#content
Technical designreferences/task-types.md#technical
Data processingreferences/task-types.md#data
Multi-skill pipelinesreferences/task-types.md#multi-skill

Skill Coordination

This is a meta-skill. It plans and monitors; domain skills do the work.

User request
  → [deep-planner] parse + plan + write TodoList to disk
      → [web search / browser] information gathering steps
      → [domain skill A] content or processing steps
      → [domain skill B] platform-specific steps
  → [deep-planner] reflection + mark file as completed

Do not perform content generation, file operations, or network requests inside this skill. Delegate those to the appropriate tools and skills.

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

93.66%
按下载量换算1,024

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

通过

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

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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