Run tests and auto-fix failures. Detects the test framework, executes tests, and iterates on fixes until all pass.
Scanned 9/4/2026
Install to Claude Code
npx -y skills add This-HW/claude-code-kit --skill test --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Test?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/this-hw-test)More formats (shields.io, HTML) on the badges page.
---
name: test
description: Run tests and auto-fix failures. Detects the test framework, executes tests, and iterates on fixes until all pass.
model: sonnet
effort: medium
---
# 테스트 실행
**즉시 실행하세요. 설명하지 말고 바로 실행합니다.**
대상: $ARGUMENTS
---
## 파이프라인 구조
```
┌──────────────┐ ┌──────────────┐ ┌──────────────┐
│ 테스트 실행 │ → │ verify-code │ → │ fix-bugs │
│ (Bash) │ │ (haiku) │ │ (sonnet) │
└──────────────┘ └──────────────┘ └──────────────┘
│ │
▼ │
실패 분석 필요 ─────────────┘
```
---
## 1단계: 프로젝트 타입 감지 및 테스트 실행
프로젝트에 맞는 테스트 명령 실행:
```bash
# Python 프로젝트
pytest $ARGUMENTS -v --tb=short
# Node.js 프로젝트
npm test $ARGUMENTS
# Go 프로젝트
go test $ARGUMENTS ./...
# Rust 프로젝트
cargo test $ARGUMENTS
```
---
## 2단계: 결과 검증
```
Task tool 사용:
subagent_type: verify-code
model: haiku
prompt: |
테스트 결과를 분석해주세요:
[테스트 실행 출력]
분석 내용:
- 총 테스트 수, 통과/실패/스킵 수
- 커버리지 (있으면)
- 실패한 테스트 목록 및 원인 분석
```
---
## 3단계: 실패 시 버그 수정
실패가 있으면 fix-bugs 에이전트로 수정:
```
Task tool 사용:
subagent_type: fix-bugs
model: sonnet
prompt: |
다음 테스트 실패를 수정해주세요:
[실패한 테스트 출력]
각 실패에 대해:
1. 실패한 테스트명
2. 에러 메시지
3. 예상 vs 실제 값
4. 코드 수정
```
---
## 출력 형식
### 테스트 결과
| 항목 | 결과 |
| --------- | ---- |
| 총 테스트 | N개 |
| 통과 | N개 |
| 실패 | N개 |
| 스킵 | N개 |
### 실패 상세 (있으면)
[테스트별 원인과 수정 방안]
### 수정 결과 (실패 시)
[fix-bugs 에이전트 적용 결과]
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!
Adversarial multi-agent planning skill. Self-orchestrates 5 hostile category members (unspecified-low, unspecified-high, deep, ultrabrain, artistry) via team-mode for ruthless cross-critique debate, distills only the defensible insights, then MANDATORILY hands the distilled insight bundle to the `plan` agent for executable plan formalization. Use when planning needs maximum rigor and surfacing of weak assumptions, blind spots, and over-engineering. Triggers: 'hyperplan', 'hpp', '/hyperplan', ...
Ultra-compressed communication mode. Cuts token usage ~75% by speaking like caveman while keeping full technical accuracy. Supports intensity levels: lite, full (default), ultra, wenyan-lite, wenyan-full, wenyan-ultra. Use when user says "caveman mode", "talk like caveman", "use caveman", "less tokens", "be brief", or invokes /caveman. Also auto-triggers when token efficiency is requested.
Routes multi-tool workflows through MCP servers for large datasets and pipelines. Use when Bash tool overhead is limiting throughput on data-heavy tasks.
**Complete production-ready guide for Google Gemini embeddings API** This skill provides comprehensive coverage of the `gemini-embedding-001` model for generating text embeddings, including SDK usage, REST API patterns, batch processing, RAG integration with Cloudflare Vectorize, and advanced use cases like semantic search and document clustering. ---
Recovers prior coding-agent session context by running `catchup <agent> --since-compact`, which extracts a clean summary of a previous Codex, Claude Code, Antigravity, OpenCode, or Pi Agent session. Use when the user says "catch up", "what did the last session do", "get me up to speed", "I switched agents", or asks to recover/summarize a previous session before continuing. Do NOT use for the current conversation, git history, or any non-agent log.