quick-rules-integrator

quick-rules-integrator is an agent for Claude Code from epoko77-ai/im-not-ai. It costs 151 tokens per session (2,072 once invoked), scanned A, original, MIT.

An integration workflow for updating a compact rulebook used by a monolithic tool, checking its limits, and preparing a GitHub pull request and changelog.

In plain words
What is it for?
Use it to combine approved source files into a new rulebook, check that it stays within the stated size and tool-call limits, record regression results, and prepare release documentation.
Why use it?
It keeps new classification, measurement, and writing-guidance changes together while protecting the existing rulebook and its definition from unintended edits.

Agent for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: model in frontmatter.

Part of the humanize-korean plugin — 3 skills, 9 agents shipped together

Good fit Use it to combine approved source files into a new rulebook, check that it stays within the stated size and tool-call limits, record regression results, and prepare release documentation.

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Install with agentmods
npx agentmods add agents/epoko77-ai/im-not-ai/quick-rules-integrator
About the project

Humanize KR is a command-line coding-agent skill that detects patterns making Korean text look machine-written and rewrites its style, rhythm, and wording while preserving the content. Korean-language writers use it to revise translation-like phrasing, repetitive structures, formulaic expressions, and other listed AI writing patterns. The catalogue includes its agents, skills, instructions, and plugin for supported coding-agent tools.

epoko77-ai/im-not-ai · 5,318 stars · on GitHub · imnotai.kr

Install

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.

Clone the repo
git clone --depth 1 https://github.com/epoko77-ai/im-not-ai

Made for: Claude Code.

Or install humanize-korean, the plugin that ships this one along with the rest of its 3 skills, 9 agents.

Wrote 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.

agentmods badge for quick-rules-integrator

README.md
[![agentmods](https://agentmods.dev/badge/agents/epoko77-ai/im-not-ai/quick-rules-integrator.svg)](https://agentmods.dev/agents/epoko77-ai/im-not-ai/quick-rules-integrator)
Your own site
<a href="https://agentmods.dev/agents/epoko77-ai/im-not-ai/quick-rules-integrator"><img src="https://agentmods.dev/badge/agents/epoko77-ai/im-not-ai/quick-rules-integrator.svg" alt="Measured on agentmods" height="20"></a>
Per session 151 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,072 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00151 $0.02072
Opus 5 $0.00076 $0.01036
Sonnet 5 $0.00030 $0.00414
Haiku 4.5 $0.00015 $0.00207

Measured 9d ago against content hash 0fb2b7224e61, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

quick-rules-integrator 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 9d 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.

agents/quick-rules-integrator.md · 137 lines

How it starts

The opening of the file, as written. The whole thing — 137 lines — stays where its author put it; the contents beside it link to each section on GitHub.

역할

taxonomist v2.0 산출물(taxonomy.md·promotion_decisions)과 metric-engineer·scholar 패치를 받아, quick-rules.md(monolith 전용 슬림 룰북)에 안착하고, monolith 도구 호출 캡 회귀를 검증하고, PR 초안·CHANGELOG를 작성한다.

입력

  • 04_taxonomy/ai-tell-taxonomy.md v2.0 (taxonomist 최종본)
  • 04_taxonomy/04_promotion_decisions.md (신규/보강 결정 기록)
  • 03_metrics/metrics_v2.py + tests
  • 03_scholar/playbook_patch.md + scholarship.md
  • 05_regression/05_regression_v2.md (회귀 검증 결과)
  • 기존 quick-rules.md (126줄, 절대 무수정 보호)
  • 기존 monolith 정의(agents/humanize-monolith.md, 무수정 검증 대상)

출력

1) _workspace/v2.0-YYYY-MM-DD/06_quickrules/quick-rules_v2.md

핵심 제약: ≤ 180줄, monolith 전용 슬림 유지.

기존 126줄 + 신규 카테고리/패턴의 룰만 ≤ 50줄 추가. 학술 인용·예문 verbatim·15항목 체크리스트 전문은 절대 반입 금지(scholarship.md·playbook.md로 분리됨).

신규 행 형식:

- A-16: "그/그녀/그것/그들" 단락 ≥ 3회 → 50%+ 영형(생략) 또는 호칭으로 (이근희·김도훈)
- A-17: 무정물·추상명사 + "-들" → 거의 모두 삭제, 분포성 강조 시만 유지 (김순영 2012)
- A-18: "~에서의/~에로의/~으로의/~에의" → 절·구로 풀어쓰기 (김정우 2007)

2) _workspace/v2.0-YYYY-MM-DD/06_quickrules/monolith_regression.md

monolith 도구 호출 캡 회귀 검증 보고서.

검증 절차:

  1. agents/humanize-monolith.md diff 확인 (변경 0건 확인)
  2. 신규 quick-rules_v2.md 줄 수 ≤ 180 확인
  3. v1.6 본질 테스트 5편 input(보존됨) 중 1편을 selectable로 monolith fast 1콜 수동 시뮬레이션 가이드 (실 실행은 사용자 명시 트리거 후)
  4. 도구 호출 cap 3회 유지 확인 (정의 파일 grep)

3) _workspace/v2.0-YYYY-MM-DD/07_pr/07_pr_draft.md

GitHub PR 초안. 형식:

# v2.0: 한국어 번역투(translationese) 학술 보고서 통합

## Summary
- 한국 번역학계 8대 번역투 유형(이근희·김정우·김도훈·김순영·김혜영·이영옥) 본진 흡수
- Toral 2019 post-editese 3축(단순화·정규화·간섭) 정량 지표 추가
- 신규 패턴 N건 (A-16 ~ A-NN), 보강 M건
- monolith 정의 무수정, 도구 호출 3회 캡 보존
- scholarship.md 신규 외부 인용 SSOT 분리, taxonomy.md 메타필드는 한 줄

## 변경 파일
- `references/ai-tell-taxonomy.md`: 490줄 → NNN줄 (신규 N·보강 M 패턴)
- `references/quick-rules.md`: 126줄 → NNN줄 (≤ 180)
- `references/metrics.py`: +13~15 함수
- `references/scholarship.md`: 신규 (학술 인용 전문)
- `references/rewriting-playbook.md`: 153줄 → NNN줄 (15PE 체크리스트 흡수)
- `tests/test_metrics_v2.py`: 신규 (≥ 20 test)
- `_workspace/v2.0-2026-05-07/`: 작업 산출물 (gitignore)

## 회귀 검증
- 기존 13 pytest 통과
- 신규 ≥ 20 pytest 통과
- v1.6 5편 점수 산출(재윤문 없음): risk_band 분포 표
- monolith 정의 diff: 0건

## v1.6 → v2.0 호환성
- 슬래시 커맨드 /humanize·/humanize-redo 그대로
- baseline 일부 placeholder (별도 회차)
- v1.6 산출물(`_workspace/2026-05-07-{001~008}/`) 보존

## 4대 철칙 준수
1. monolith·5인 정의 무수정 ✅
2. 재윤문 없는 회귀 ✅
3. 학술 인용 양면 보존 (SSOT 메타 + scholarship.md) ✅
4. 카테고리 분리 자율 판정 (taxonomist 결정 기록) ✅

## 미해결 이월
- baseline 실측 교정 (계속)
- v1.5 strict 모드 회귀 (계속)
- 사용자 블라인드 판정

Read the full file on GitHub · 137 lines

Changes

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.

  1. 9d ago First seen · 137 lines · 151 tokens per session scan A 0fb2b7224e61

Subscribe to this mod's changes

quick-rules-integrator is an agent published in the GitHub repository epoko77-ai/im-not-ai (5,318 stars, last pushed 2d ago), licensed MIT. It adds 151 tokens to every session and 2,072 once invoked, about $0.0008 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 2026-08-30.