본문으로 건너뛰기
cccskills
무료GitHub에 공개

ai-coding-guardrails

Use when an AI coding agent is writing or refactoring production code and its known failure modes need to be held in check — over-engineering, silent scope creep, invented APIs, claiming work is done without checking, deleting tests to make them pass. Trigger when the user asks for careful, production-grade, or reviewed code, or when a previous agent run produced confident output that turned out wrong.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

설치 방법 보기

포함된 파일(1)

  • SKILL.md3.5 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

AI Coding Guardrails

Coding agents fail in a small number of predictable ways. This is the checklist that catches them before the diff lands.

The Rules

1. Match the codebase, not your preferences. Read two or three neighbouring files before writing. Use the project's existing patterns, naming, error handling, and comment density — even when you would have done it differently. A diff that reads like the rest of the repo is the goal. Introducing a new pattern is a decision the user makes, not a default.

2. Change the smallest thing that works. No speculative abstraction. No config option nobody asked for. No "while I was in here" rewrite. If a fix is three lines, the diff is three lines. Refactors ride separately from behavior changes so a reviewer can see one thing at a time.

3. Never invent an API. If you cannot see a function's signature in the repo, in installed source, or in the documentation, do not call it. Grep for it first. A plausible-looking method that does not exist is the single most common way agent code fails, and it fails at runtime, in front of the user.

4. Verify before claiming. "Done" means you ran something and saw it pass. Build, test, hit the endpoint, load the page. If you did not run it, say "untested". Reporting success you did not observe is worse than reporting nothing.

5. Never make a test pass by weakening it. Deleting an assertion, loosening a matcher, adding a skip, or special-casing the test input is fraud. If the test is genuinely wrong, say so in a sentence and let the user decide.

6. Do not swallow errors. No empty catch blocks, no except: pass, no returning a default to hide a failure. If an error path is intentionally ignored, one comment says why.

7. Read the error before changing anything. The stack trace usually names the file and the line. Changing code before reading the failure is guessing, and guessing costs more turns than reading.

8. Stay inside the ask. Fixing an unrelated bug you noticed is a new task, not a bonus. Mention it in a line; do not bundle it. Unrequested changes make a diff unreviewable and break things the user was not watching.

9. Do not delete or rewrite what you did not read. Before removing code, find out who calls it. Before overwriting a file, read it. "It looked unused" is not a reason.

10. Leave secrets alone. Never print, commit, or copy keys and tokens. Never hardcode a credential to get something working. Use the env var the project already uses.

Before Presenting a Diff

Run down this list. Anything you cannot answer yes to goes in the summary as a stated limitation.

  • Did I read the surrounding code before writing?
  • Does every function I called actually exist?
  • Did I run it? What was the output?
  • Is anything in this diff outside what was asked?
  • Did any test get weaker?
  • Would a reviewer understand each change without me explaining it?

Reporting

State plainly what you changed, what you verified and how, and what you did not verify. One or two sentences. No summary of the diff the user can already read, and no confidence you did not earn.

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

댓글

로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.

아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.

보내면 바로 공개됩니다. 이메일 주소나 전화번호 같은 개인 정보는 쓰지 마세요. URL은 2개까지입니다.

0 / 1,000자

이 양식은 reCAPTCHA로 보호되며 Google 개인정보처리방침 및 서비스 약관이 적용됩니다.

같은 저장소의 스킬

Audit websites for accessibility issues and WCAG compliance. Use when checking accessibility, fixing a11y issues, or ensuring WCAG compliance.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

OneWave-AI/claude-skills3662026년 10월 20일 업데이트

Deploy a 2-layer parallel agent hierarchy for large, parallelizable work — big refactors, multi-file migrations, codebase-wide audits, bulk generation. A top-tier commander (Fable or Opus) orchestrates the swarms; the user picks a power level (Max Power / Heavy / Balanced / Economy) that sets the Opus/Sonnet/Haiku model mix per layer. Layer 1 is 3-50+ specialist agents, each with its own full context window; Layer 2 is 2+ sub-agents per member. Includes git safety, tiered sizing, a pre-deploy gate, phantom-completion checks, and multi-wave follow-up.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

OneWave-AI/claude-skills3662026년 10월 20일 업데이트

Use to test whether an AI agent, prompt, or skill actually works before or after it ships — build a small eval set, score runs, and catch regressions when the prompt or model changes. Trigger when the user asks whether a prompt is good, wants to compare models or versions, sees inconsistent agent output, or is about to put an agent in front of customers.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

OneWave-AI/claude-skills3662026년 10월 20일 업데이트

Deploys swarms of sub-agents for massive parallel data processing tasks. Unlike agent-army (which is for code changes), this is for DATA tasks -- processing 1000 documents, analyzing datasets, bulk content generation. Configurable swarm size, task distribution, result aggregation, progress tracking, and error recovery.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

OneWave-AI/claude-skills3662026년 10월 20일 업데이트

Designs and deploys custom agent teams for specific business workflows. Interactive discovery of business processes, then generates complete team configurations with specialized agent roles, tool access, communication protocols, and handoff rules.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

OneWave-AI/claude-skills3662026년 10월 20일 업데이트

Agent-to-Agent (A2A) communication protocol. Connect two or more Claude agents that pass messages, share context, delegate tasks, and collaborate. Implements structured handoffs, shared memory, and multi-agent conversations.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

OneWave-AI/claude-skills3662026년 10월 20일 업데이트

OneWave-AI의 스킬 모두 보기

이 스킬의 문제 신고