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Plan

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jh941213
plan

복잡한 작업(3단계 이상 구현 또는 아키텍처 결정 포함) 전 계획 수립. Plan 모드에서 사용하거나 자동 활성화. 트리거: "계획", "플랜", "어떻게 구현", "설계", "아키텍처 결정" 안티-트리거: "바로 구현해", "간단한 수정", "마이크로 수정"

Overview

Publisherjh941213
Repositorymy-cc-harness
Skill nameplan
Stars
125
Forks
35
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by jh941213 on GitHub. Read the source before you install it.

Installation

Install the Plan AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/jh941213/my-cc-harness.git /tmp/my-cc-harness
mkdir -p .claude/skills
cp -r /tmp/my-cc-harness/skills/plan .claude/skills/plan
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Plan in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Plan on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Plan is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

작업 계획 수립

새로운 기능이나 복잡한 작업을 시작하기 전에 계획을 세웁니다.

언제 Plan을 사용하는가

상황Plan 필요대신 사용
3단계 이상 구현O
아키텍처 결정 포함O
여러 파일 변경O
1-2줄 수정X바로 구현
버그 수정 (원인 명확)X바로 수정
"무엇을 만들까" 결정X/prd 사용
기술 명세서 필요X/spec 사용

계획 수립 프로세스

1. 요구사항 분석

  • 성공 기준 정의 ("완료"란 무엇인가?)
  • 가정과 제약사항 명시
  • 스코프 경계 설정 (하지 않을 것도 명시)

2. 현재 코드 파악

  • 관련 파일/함수 탐색 (Grep, Glob)
  • 기존 패턴과 컨벤션 파악
  • 유사한 구현 검토

3. 접근 방식 비교

  • 최소 2개 방안 제시
  • 각 방안의 트레이드오프 분석
  • 추천 방안 선택 + 이유

4. 작업 분해

각 단계에 포함:

  • 구체적 작업 (파일 경로, 함수명)
  • 의존성 (선행 단계)
  • 예상 복잡도 (Low/Med/High)
  • 검증 방법

5. 위험 요소 + 완화책

출력 형식

markdown
## 요구사항 요약
- 성공 기준: ...
- 스코프: ...
- 하지 않을 것: ...

## 접근 방식
- **방안 A**: ... (추천)
- **방안 B**: ...
- 선택 이유: ...

## 구현 단계

### 1단계: [단계명] (Low)
- 작업: ...
- 파일: path/to/file.ts
- 의존성: 없음
- 검증: `npm run typecheck`

### 2단계: [단계명] (Med)
- 작업: ...
- 의존성: 1단계
- 검증: `npm test`

## 수정할 파일
- 파일1: 변경 내용
- 파일2: 변경 내용

## 위험 요소
- **위험**: [설명] → **완화**: [대책]

## 테스트 전략
- 단위: ...
- 통합: ...

계획 확정 후

  1. 사용자 승인 대기
  2. 계획을 docs/execute-plans/에 저장 — ~/.claude/templates/execute-plan.md.template 형식 사용
  3. 승인 시 CHECKPOINT.md 생성 (3단계 이상일 때)
  4. 3단계 이상 계획이면 교차 모델 검토(~/.claude/rules/cross-model-verification.md) 수행
  5. 실수 발생 시 즉시 STOP → re-plan (밀어붙이지 않기)

Frequently asked questions

What does the Plan AI skill do?

복잡한 작업(3단계 이상 구현 또는 아키텍처 결정 포함) 전 계획 수립. Plan 모드에서 사용하거나 자동 활성화. 트리거: "계획", "플랜", "어떻게 구현", "설계", "아키텍처 결정" 안티-트리거: "바로 구현해", "간단한 수정", "마이크로 수정"

Why use Plan on TypingMind?

Because you install it once and use it with any model. Plan is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Plan in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/jh941213/my-cc-harness/tree/main/skills/plan. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Plan?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Plan?

As many as you like. As long as a model supports skills, you can use Plan with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Plan AI skill free?

It is published on GitHub by jh941213. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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