rule_selector

rule_selector is a cursor rule for Cursor from gaebalai/Cursor-DEF-A-Rule. It costs 3,282 tokens per session, scanned A, original, MIT.

A rule-selection guide that matches words and request types to DEF-A stages, technical areas, and communication styles.

In plain words
What is it for?
Use it to route questions about requirements, design, implementation, testing, research, frontend or backend work, knowledge management, and ethical concerns.
Why use it?
It helps choose relevant guidance instead of applying every development rule to every request.

Cursor rule for Cursor

Written for Cursor: a Cursor rule (.mdc).

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.

agentmods
npx agentmods add rules/gaebalai/cursor-def-a-rule/rule_selector
Clone the repo
git clone --depth 1 https://github.com/gaebalai/Cursor-DEF-A-Rule

Made for: Cursor.

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 rule_selector

README.md
[![agentmods](https://agentmods.dev/badge/rules/gaebalai/cursor-def-a-rule/rule_selector.svg)](https://agentmods.dev/rules/gaebalai/cursor-def-a-rule/rule_selector)
Your own site
<a href="https://agentmods.dev/rules/gaebalai/cursor-def-a-rule/rule_selector"><img src="https://agentmods.dev/badge/rules/gaebalai/cursor-def-a-rule/rule_selector.svg" alt="Measured on agentmods" height="20"></a>
Per session 3,282 This file is loaded in full into every session.
When invoked 3,282 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
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 $0.03282 $0.03282
Opus 5 $0.01641 $0.01641
Sonnet 5 $0.00656 $0.00656
Haiku 4.5 $0.00328 $0.00328

Measured 6d ago against content hash 9efb7112f981, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

rule_selector 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 6d 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.

rules/defa/rule_selector.mdc · 211 lines

How it starts

The opening of the file, as written. The whole thing — 211 lines — stays where its author put it; the contents beside it link to each section on GitHub.

MIT License - https://opensource.org/licenses/MIT

[SELECTOR] 질문 내용에 따른 규칙 선택 시스템 (DEF-A 통합 최적화 버전)

DEF-A 질문 분석 프레임워크 (최적화 버전)

DEF-A 단계 판정 키워드 (부분 적용 대응)
🎯 Define 단계: "요구사항", "문제", "과제", "이해", "무엇을", "왜", "전략", "설계"
🔍 Explore 단계: "비교", "선택", "어느 쪽", "검토", "학습", "이해", "단계별"
✨ Formulate 단계: "설계", "구조", "통합", "최적화", "구현", "개발", "타입 안정성"
📝 Act/Apply 단계: "구현", "코딩", "작성", "실행", "긴급", "수정", "버그"
📈 Assess/Adjust 단계: "평가", "측정", "분석", "개선", "프로세스 최적화"
인지 스타일 판정 키워드 (최적화 버전)
Systems Mode: "시스템", "아키텍처", "설계", "전략", "복잡", "타입 안정성", "효율적"
Empathy Mode: "사용자", "경험", "학습", "교육", "팀", "단계별", "실용적"
기술 영역 판정 키워드 (최적화 버전)
프론트엔드: React, Vue, Angular, TypeScript, JavaScript, 컴포넌트, UI, UX
백엔드: API, 서버, 데이터베이스, Node.js, Python, 인증, 보안
테스트: 테스트, TDD, BDD, Jest, Vitest, 품질 보증, 리뷰, CI/CD
지식 관리: 암묵지, 형식지, SECI 모델, 지식 공유, 학습, 베스트 프랙티스, 규칙화
윤리적 고려: 윤리, 편향, 포용성, 공정성, 인간성, 다양성, 공감, 상호 학습
전반・설계: 설계, 아키텍처, 패턴, 최적화, 보안, 풀스택
질문 유형 판정 (최적화 버전)
구현・코딩: "구현", "코드", "작성", "개발", "에러", "버그", "수정"
설계・아키텍처: "설계", "아키텍처", "구조", "패턴", "선택", "비교"
테스트・품질: "테스트", "품질", "검증", "TDD", "BDD", "리뷰", "개선"
조사・학습: "조사", "리서치", "학습", "비교", "단계별", "이해", "실습"
긴급 대응: "긴급", "운영", "크래시", "에러", "수정", "최소화", "신속"
에러 처리: "에러", "예외", "장애", "디버깅", "로그", "모니터링"
팀 협업: "팀", "협업", "리뷰", "페어", "멘토링", "공유", "학습"
지식 관리: "암묵지", "형식지", "SECI", "지식 공유", "학습", "베스트 프랙티스", "규칙화"
윤리적 고려: "윤리", "편향", "포용성", "공정성", "인간성", "다양성", "공감", "상호 학습"
프로그래밍 윤리: "함수명", "변수명", "주석", "에러 메시지", "코드 리뷰", "네이밍 규칙", "문서화"

DEF-A 통합 규칙 선택 로직 (최적화 버전)

우선순위 기반 규칙 적용
1. DEF-A 단계 판정 → 사고 흐름 단계 결정 (완전/부분/최소 적용)
2. 인지 스타일 판정 → 응답 스타일 결정 (Systems/Empathy)
3. 기술 영역 판정 → 전문 규칙 파일 선택
4. 질문 유형 판정 → 적용 수준 결정
5. 긴급도 판정 → 복잡성 조정
6. 프로젝트 특성 → 맞춤형 적용
7. 부분 적용 전략 → 효율성 최적화
DEF-A 단계별 규칙 적용 매트릭스 (최적화 버전)
DEF-A 단계 → 적용 규칙・접근법・복잡성
├── 🎯 Define → 요구사항 분석・문제 정의・맥락 이해 (완전 적용 시에만)
├── 🔍 Explore → 다각도 분석・기술 선택・접근법 검토 (학습 지원 시 강조)
├── ✨ Formulate → 설계 통합・최적화・구현 계획 (구현 중시 시)
├── 📝 Act/Apply → 구현・코딩・통합 (긴급 대응 시 최소화)
└── 📈 Assess/Adjust → 평가・개선・최적화 (프로세스 개선 시 강조)

Read the full file on GitHub · 211 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. 6d ago First seen · 211 lines · 3,282 tokens per session scan A 9efb7112f981

Subscribe to this mod's changes

rule_selector is a cursor rule published in the GitHub repository gaebalai/Cursor-DEF-A-Rule (12 stars, last pushed 1y ago), licensed MIT. It adds 3,282 tokens to every session, about $0.0164 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.