Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add mupengi-bot/mupengism --skill mupeng-learngit clone --depth 1 https://github.com/mupengi-bot/mupengismWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/mupengi-bot/mupengism/mupeng-learn)<a href="https://agentmods.dev/skills/mupengi-bot/mupengism/mupeng-learn"><img src="https://agentmods.dev/badge/skills/mupengi-bot/mupengism/mupeng-learn/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/mupengi-bot/mupengism/mupeng-learn"><img src="https://agentmods.dev/badge/skills/mupengi-bot/mupengism/mupeng-learn.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00036 | $0.02382 |
| Opus 5 | $0.00018 | $0.01191 |
| Sonnet 5 | $0.00007 | $0.00476 |
| Haiku 4.5 | $0.00004 | $0.00238 |
Grade A, and why
mupeng-learn scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 343 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Mupeng Learn — 학습 수집 스킬
개요
서브에이전트들과 다른 에이전트들이 생성한 인사이트와 학습 결과를 자동으로 수집하고, 무펭이의 메모리 시스템에 통합한다.
"에이전트들의 집단 학습"을 구현하는 핵심 스킬.
문제 인식
현재 OpenClaw에서:
- 서브에이전트들이 작업하면서 얻은 교훈이 사라짐
- 같은 실수를 반복함
- 한 에이전트가 배운 것을 다른 에이전트가 모름
- 학습이 축적되지 않고 휘발됨
예시:
서브에이전트 A: "아, CLI 실행할 때 PYTHONPATH 설정해야 하는구나"
→ 세션 종료
→ 메모리 증발
서브에이전트 B (다음날): "왜 CLI가 안 돌아가지?"
→ 같은 문제 다시 겪음
핵심 기능
1. 인사이트 자동 수집
서브에이전트가 작업 완료 시 자동으로 학습 리포트 생성:
learn_report:
session_id: "subagent-abc123"
task: "Instagram DM CLI 구현"
insights:
- type: "mistake"
description: "브라우저 CDP 연결 시 타임아웃 설정 필수"
lesson: "puppeteer.connect() 시 timeout: 60000 필수"
- type: "optimization"
description: "DOM 파싱보다 API 직접 호출이 95% 토큰 절약"
lesson: "Internal API 사용 우선 검토"
files_modified:
- "/workspace/tools/insta-cli/v2.js"
cost:
tokens_used: 12000
time_seconds: 180
2. 지식 통합
수집된 인사이트를 무펭이 메모리에 자동 통합:
저장 위치:
memory/learnings/YYYY-MM-DD.md— 일별 학습 로그memory/knowledge-base.json— 구조화된 지식 베이스TOOLS.md,AGENTS.md— 관련 문서 자동 업데이트
예시 (knowledge-base.json):
{
"cli_tools": {
"best_practices": [
{
"rule": "외부 API 직접 호출 > 브라우저 자동화",
"reason": "토큰 95% 절약, 속도 10배 향상",
"source": "subagent-abc123",
"learned_at": "2026-02-07T08:00:00Z"
}
]
}
}
3. 패턴 인식
반복되는 실수/해결책을 자동으로 감지:
패턴 감지:
- "CDP 타임아웃" 이슈 → 3번 발생
- 해결책 → 매번 동일
→ 자동으로 TOOLS.md에 경고 추가
→ 다음 에이전트는 미리 알고 시작
4. 크로스-에이전트 학습
다른 무펭이즘 에이전트들의 학습도 수집:
[MUPENGISM_LEARNING]
from: Claude-Sonnet-API-instance
model: claude-3-sonnet
task: "Twitter 자동화"
lesson:
"트윗 전송 전 반드시 dry-run 플래그로 테스트.
실수로 100개 트윗 보낸 경험 있음."
[/MUPENGISM_LEARNING]
기술 구현
Architecture
┌─────────────────┐
│ Subagent 종료 │ ── learn_report 생성
└────────┬────────┘
│
▼
┌─────────────────────┐
│ mupeng-learn 수집 │ ── JSON 파싱
└────────┬────────────┘
│
▼
┌─────────────────────┐
│ 지식 베이스 업데이트 │ ── knowledge-base.json
└────────┬────────────┘
│
▼
┌─────────────────────┐
│ 관련 문서 자동 수정 │ ── TOOLS.md, AGENTS.md
└─────────────────────┘
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 343 lines · 36 tokens per session scan A 0ec13706bd09
mupeng-learn is a skill published in the GitHub repository mupengi-bot/mupengism (10 stars, last pushed 2mo ago), licensed MIT. It adds 36 tokens to every session and 2,382 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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