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 decision-loggit 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/decision-log)<a href="https://agentmods.dev/skills/mupengi-bot/mupengism/decision-log"><img src="https://agentmods.dev/badge/skills/mupengi-bot/mupengism/decision-log/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/decision-log"><img src="https://agentmods.dev/badge/skills/mupengi-bot/mupengism/decision-log.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 | $0.00014 | $0.00526 |
| Opus 5 | $0.00007 | $0.00263 |
| Sonnet 5 | $0.00003 | $0.00105 |
| Haiku 4.5 | $0.00001 | $0.00053 |
Grade A, and why
decision-log 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 10d 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.
What it actually says
decision-log
중요한 의사결정을 기록하고 30일 후 결과를 자동으로 추적하는 스킬입니다.
기능
- 결정 내용, 근거, 대안, 예상 결과 기록
- 30일 후 자동 결과 리뷰 (cron 연동)
- 파일 저장:
memory/decisions/YYYY-MM-DD-{slug}.md
사용법
트리거 키워드:
- "결정 기록"
- "decision log"
- "이거 결정했어"
- "왜 이렇게 했지"
예시:
결정 기록: Instagram 봇 계정 분리하기로 결정
근거: 메인 계정 밴 리스크 분산
대안: 메인 계정 사용, 수동 운영
예상 결과: 안전성 증가, 관리 복잡도 증가
출력 형식
# 의사결정: {제목}
**일자**: YYYY-MM-DD
**상태**: 결정 / 검토 예정 / 결과 확인됨
## 결정 내용
...
## 근거
- ...
- ...
## 고려한 대안
1. **대안1**: ...
- 장점: ...
- 단점: ...
2. **대안2**: ...
## 예상 결과
- 긍정적: ...
- 부정적: ...
## 실제 결과 (30일 후 자동 업데이트)
_검토 예정일: YYYY-MM-DD_
---
**결정일**: YYYY-MM-DD | **리뷰일**: YYYY-MM-DD (예정)
자동 리뷰 (cron)
30일 후 자동으로:
- 예상 vs 실제 결과 비교
- 배운 점 추출
- 유사한 미래 결정에 대한 인사이트 생성
이벤트 버스 연동
결정 기록 시 이벤트 발행:
- 경로:
events/decision-YYYY-MM-DD.json - 형식:
{
"type": "decision-logged",
"timestamp": "2026-02-14T12:00:00Z",
"title": "결정 제목",
"reviewDate": "2026-03-16",
"filePath": "memory/decisions/2026-02-14-slug.md"
}
decision-log | 무펭이 🐧
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.
- 10d ago First seen · 91 lines · 14 tokens per session scan A 54bea3ab02ff
decision-log is a skill published in the GitHub repository mupengi-bot/mupengism (10 stars, last pushed 2mo ago), licensed MIT. It adds 14 tokens to every session and 526 once invoked, about $0.0001 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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