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Deep Planner

A meta-skill that activates before complex tasks to enforce structured planning, step-by-step execution, and self-reflection. Works like Claude Code's TodoLi...
元技能:在复杂任务前启动,强制结构化规划、分步执行和自我反思,类似 Claude Code 的 TodoList。
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概述

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.

版本历史

共 1 个版本

  • v1.0.2 当前
    2026-05-07 05:33 安全 安全

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