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Compact Guide

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jh941213
compact-guide

컨텍스트 윈도우 관리 및 토큰 최적화 가이드. Triggers on: 컨텍스트, 토큰, compact, 메모리 관리. NOT for: 코드 작성, 디버깅.

Overview

Publisherjh941213
Repositorymy-cc-harness
Skill namecompact-guide
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 Compact Guide 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/compact-guide .claude/skills/compact-guide
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Compact Guide 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 Compact Guide 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 Compact Guide 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.

컨텍스트 관리 가이드

컨텍스트는 신선한 우유와 같습니다. 양이 아니라 신선도가 문제입니다 — 오염된 컨텍스트는 리셋이 낫습니다.

핵심 원칙 (1M 컨텍스트 시대)

  • 토큰 잔량을 세지 않는다 — auto-compact가 임계값을 관리한다 — 수동 /compact는 작업 단위가 끝나는 시점에만
  • 수동 개입은 수치가 아니라 신호 기반으로:
신호행동
작업 단위(마일스톤/스토리)가 끝났다/compact — 다음 단위를 깨끗하게 시작
작업 주제가 완전히 바뀐다/handoff → /clear — 새 세션
같은 실수 반복, 이전 결정 망각, 비논리적 응답오염 신호 — /handoff → /clear (compact로는 오염이 안 씻긴다)
긴 탐색/로그 출력 직후작업 단위가 끝나는 시점이면 /compact, 아니면 auto-compact에 맡김
  • 남은 컨텍스트 걱정으로 작업을 축소하거나 서두르지 않는다 — 계속 진행

명령어

/compact

  • 대화 내용을 요약해서 압축
  • 중요한 정보는 유지, 토큰만 줄임
  • 작업 흐름이 끊기지 않음

/clear

  • 완전히 초기화
  • HANDOFF.md 없으면 위험!
  • 깨끗하게 시작하고 싶을 때

권장 패턴

작업 시작
작업 단위 완료 (마일스톤/스토리)
/compact (단위 경계에서 정리)
… 반복 …
주제 전환 or 오염 신호
/handoff (HANDOFF.md 생성)
/clear (초기화)
새 세션에서 HANDOFF.md 읽기

비용 관점의 컨텍스트 관리

/compact가 유리한 이유

  • 작업 맥락(진행 상황·결정사항)이 요약으로 유지되어 다시 쌓을 필요가 없음
  • 중요 정보는 남기고 토큰만 줄이므로 작업 흐름이 끊기지 않음
  • /clear보다 재시작 비용이 낮음

/clear의 숨겨진 비용

  • 대화 컨텍스트 재구축 비용 — 진행 상황·결정사항·탐색 결과를 처음부터 다시 쌓아야 함
  • HANDOFF.md 로드 시 추가 토큰 발생
  • HANDOFF.md에 담기지 않은 암묵적 맥락은 유실됨

판단 기준

  • 비용만 보면: /compact > /clear
  • 품질이 흔들리면: /clear가 정답 — 오염된 컨텍스트를 요약하면 오염도 요약된다
  • 장시간 자율 실행(TTH/autodev)은 auto-compact에 맡기고 개입하지 않는다

Frequently asked questions

What does the Compact Guide AI skill do?

컨텍스트 윈도우 관리 및 토큰 최적화 가이드. Triggers on: 컨텍스트, 토큰, compact, 메모리 관리. NOT for: 코드 작성, 디버깅.

Why use Compact Guide on TypingMind?

Because you install it once and use it with any model. Compact Guide 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 Compact Guide in TypingMind?

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

Which AI models can use Compact Guide?

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 Compact Guide?

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

Is the Compact Guide 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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