alber70g/skills

general-guidelines

Behavioral guidelines to reduce common LLM coding mistakes.

소스 보기

사용 방법

  1. 설치 명령을 복사하고 자신의 에이전트 환경에 설치하기 전에 소스 패키지를 확인하세요.
  2. 필요한 도구, 인증 정보, 지원 환경은 원본 문서에서 확인하세요.
  3. 입력과 원하는 산출물을 설명하고 출처와 결과를 대조하세요.
npx skills add https://github.com/alber70g/skills --skill general-guidelines

시작 전 확인

  • 설치에는 모델 구독, API 한도, 파일 접근 권한이 포함되지 않습니다.
  • 별점 수와 설치 수는 활동 지표이며 독립적인 품질·보안 검증이 아닙니다.
원본 Skill 문서

원본 저장소의 제목, 예시, 코드, 표, 링크, 이미지를 유지해 표시합니다.

Karpathy Guidelines

Behavioral guidelines to reduce common LLM coding mistakes, derived from Andrej Karpathy's observations on LLM coding pitfalls.

Tradeoff: These guidelines bias toward caution over speed. For trivial tasks, use judgment.

1. Think Before Coding

Don't assume. Don't hide confusion. Surface tradeoffs.

Before implementing:

  • State your assumptions explicitly. If uncertain, ask.
  • If multiple interpretations exist, present them - don't pick silently.
  • If a simpler approach exists, say so. Push back when warranted.
  • If something is unclear, stop. Name what's confusing. Ask.

2. Simplicity First

Minimum code that solves the problem. Nothing speculative.

  • No features beyond what was asked.
  • No abstractions for single-use code.
  • No "flexibility" or "configurability" that wasn't requested.
  • No error handling for impossible scenarios.
  • If you write 200 lines and it could be 50, rewrite it.

Ask yourself: "Would a senior engineer say this is overcomplicated?" If yes, simplify.

3. Surgical Changes

Touch only what you must. Clean up only your own mess.

When editing existing code:

  • Don't "improve" adjacent code, comments, or formatting.
  • Don't refactor things that aren't broken.
  • Match existing style, even if you'd do it differently.
  • If you notice unrelated dead code, mention it - don't delete it.

When your changes create orphans:

  • Remove imports/variables/functions that YOUR changes made unused.
  • Don't remove pre-existing dead code unless asked.

The test: Every changed line should trace directly to the user's request.

4. Goal-Driven Execution

Define success criteria. Loop until verified.

Transform tasks into verifiable goals:

  • "Add validation" → "Write tests for invalid inputs, then make them pass"
  • "Fix the bug" → "Write a test that reproduces it, then make it pass"
  • "Refactor X" → "Ensure tests pass before and after"

For multi-step tasks, state a brief plan:

1. [Step] → verify: [check]
2. [Step] → verify: [check]
3. [Step] → verify: [check]

Strong success criteria let you loop independently. Weak criteria ("make it work") require constant clarification.

5. Keep a WORKLOG.md

Leave a trail the next session can pick up.

Every project keeps a WORKLOG.md in the relevant subdirectory (the project root, or the package/app directory in a monorepo), referenced from that directory's AGENTS.md. If it's missing, create it and add the reference.

  • Read it before starting work.
  • Update it after significant changes: what was done, what's verified, what's left.
  • When the user asks for it mid-task, update it so the work can be continued properly in a fresh session.
  • Transient notes (in-progress state, temporary workarounds, open questions) can be removed once they're no longer relevant.

6. Write Research to research/ and Plans to docs/

Findings and plans live in files, not only in the chat.

Store them next to WORKLOG.md (the project root, or the package/app directory in a monorepo). Use descriptive filenames that name the topic, such as research/sqlite-vs-postgres-for-local-first-sync.md.

  • research/: excerpts of the research you did, whether on your own (reading code, docs, running experiments) or with Tavily and/or Exa. Keep the relevant quotes and findings, with their sources, plus your conclusions.
  • docs/: the plans you make, written so the user can review them before implementation starts.
  • Before starting research, check research/ for an existing document on the topic, and ask the user whether to build on it.
  • Reference the new or updated documents in WORKLOG.md.

관련 작업

같은 저장소의 Skills

더 많은 Skills

모든 Skills
alber70g
커뮤니티

orchestrator

Session mode where the main thread orchestrates: subagents on a cheaper model do research and execution, the main thread plans and validates. Use when the user runs /orchestrator, asks you to act as an orchestrator, asks to keep the main thread token-efficient, requests a large implementation plan or a large research task, or wants you to work toward an overarching goal.

1시간 설치 수
1
GitHub Stars
0
업데이트
10월 18일
alber70g
커뮤니티

turn-based-discovery

Use the AskUserQuestion tool (the same multiple-choice mechanism plan mode uses) to get clarity from the user. Each question is multiple-choice plus a free-format "Other" escape. Ask in small batches — up to 4 questions per call (the tool's max), more if needed across calls. Use when scoping work, resolving ambiguity, or surfacing answers a research pass already raised. Triggers: /turn-based, ask me, clarify, discovery mode, interview me.

1시간 설치 수
2
GitHub Stars
0
업데이트
10월 18일
alber70g
커뮤니티

autoresearch

Autonomous experimentation skill — agent interviews the user, sets up a lab, then explores freely (think, test, reflect) until stopped or a target is hit. Works for any domain where you can measure or evaluate a result.

1시간 설치 수
1
GitHub Stars
0
업데이트
10월 18일
alber70g
커뮤니티

deepseek-harness-plugin-dev

Create, modify, debug, review, scaffold, test, and package DeepSeek Harness (dsh) plugins built on Cordis. Use when working with DeepSeek Harness plugins, Cordis plugins, cordis.yml or cordis.patch.yml, model-callable tools, services/providers, events, capability layering, plugin bundles, profiles, HMR, or dsh plugin installation.

1시간 설치 수
1
GitHub Stars
0
업데이트
10월 18일