LLM Mart Basic
@llm-mart · Joined Jun 2026
빌드·테스트 파이프라인 실행 후 통과/실패 보고 전담. 코드 절대 수정 금지. /sdlc-cycle 커맨드의 검증 단계 서브에이전트.
Imported from leeyudok/agents-scaffold/presets/lang-en/base/.claude/agents/README.md.
Meta-agent that revises other subagent definitions under .claude/agents/*.md based on feedback from actually using them. Invoke when a subagent got something wrong, produced a poor result, its description doesn't match how it's actually being invoked, or a newly discovered pitfal
Reviews code changes before merge for bugs, security, and quality. Recommends blocking merge if any CRITICAL finding surfaces.
Verifies DB schema change safety. Assesses risk before ALTER TABLE, generates rollback SQL, checks FK consistency. Invoke when migration files are added or modified.
Owns minimum-scope implementation based on the spec/issue. Does not write or run tests (owned by sdlc-tester). Development-stage subagent for the /sdlc-cycle command.
Owns writing test code against the issue's AC/TC. Does not modify implementation code or run tests (owned by sdlc-verifier). Test-stage subagent for the /sdlc-cycle command.
Owns running the build/test pipeline and reporting pass/fail. Never modifies code. Verification-stage subagent for the /sdlc-cycle command.
Persistent file-based planning for multi-step AI-agent work. Keeps task_plan.md, findings.md, and progress.md on disk; lifecycle hooks inject selected project planning context. Automatic recovery reads project planning files only. Explicit session-catchup.py --metadata reads same
Persistent file-based planning for multi-step AI-agent work. Keeps task_plan.md, findings.md, and progress.md on disk; lifecycle hooks inject selected project planning context. Automatic recovery reads project planning files only. Explicit session-catchup.py --metadata reads same
Persistent file-based planning for multi-step AI-agent work. Keeps task_plan.md, findings.md, and progress.md on disk; lifecycle hooks inject selected project planning context. Automatic recovery reads project planning files only. Explicit session-catchup.py --metadata reads same
Persistent file-based planning for multi-step AI-agent work. Keeps task_plan.md, findings.md, and progress.md on disk; lifecycle hooks inject selected project planning context. Automatic recovery reads project planning files only. Explicit session-catchup.py --metadata reads same
Persistent file-based planning for multi-step AI-agent work. Keeps task_plan.md, findings.md, and progress.md on disk; agent instructions read selected project planning context when invoked. Automatic recovery reads project planning files only. Explicit session-catchup.py --metad
Persistent file-based planning for multi-step AI-agent work. Keeps task_plan.md, findings.md, and progress.md on disk; lifecycle hooks inject selected project planning context. Automatic recovery reads project planning files only. Explicit session-catchup.py --metadata reads same
Persistent file-based planning for multi-step AI-agent work. Keeps task_plan.md, findings.md, and progress.md on disk; lifecycle hooks inject selected project planning context. Automatic recovery reads project planning files only. Explicit session-catchup.py --metadata reads same
Persistent file-based planning for multi-step AI-agent work. Keeps task_plan.md, findings.md, and progress.md on disk; Gemini lifecycle hooks inject selected project planning context. Automatic recovery reads project planning files only. Explicit session-catchup.py --metadata rea
Persistent file-based planning for multi-step AI-agent work. Keeps task_plan.md, findings.md, and progress.md on disk; lifecycle hooks inject selected project planning context. Automatic recovery reads project planning files only. Explicit session-catchup.py --metadata reads same
Persistent file-based planning for multi-step AI-agent work. Keeps task_plan.md, findings.md, and progress.md on disk; lifecycle hooks inject selected project planning context. Automatic recovery reads project planning files only. Explicit session-catchup.py --metadata reads same
AI가 쓴 한글 텍스트를 자연스럽게 윤문하는 진입 명령. humanize-korean 파이프라인을 Fast 모드(기본)로 실행하고 `--strict`면 정밀 3콜(진단→겨냥 윤문→finalize). 트리거 — "/humanize".
AI(ChatGPT·Claude·Gemini 등)가 쓴 한글 텍스트를 "사람이 쓴 글처럼" 윤문해주는 오케스트레이터 스킬. 번역투·영어 인용 과다·기계적 병렬·관용구·피동태 남용·접속사 남발·리듬 균일성·이모지/불릿 과다 등 10대 카테고리 70개 AI 티 패턴을 탐지·분류해 내용은 한 글자도 건드리지 않고 문체·리듬·표현만 자연스러운 한국어로 재작성한다. shim의 route_hint(light|standard|heavy)로 경로를 정해 잘 쓴 글은 1콜, 표준은 2콜, 중증·장문만 3+콜(진단
/tree-ring-certify
Tree ring certify
Generate Tree Ring harness or recall-quality evidence without confusing it with the full framework release suite
/tree-ring-dox-sync
Tree ring dox sync
Preview and synchronize DOX-style AGENTS.md guidance as source-linked Tree Ring memory
/tree-ring-recall
Tree ring recall
Recall durable Tree Ring Memory context before starting or resuming work
/tree-ring-status
Tree ring status
Check receipt-backed Tree Ring harness readiness without claiming configuration is activation
/browser-debug
Browser debug
Запусти Яндекс Браузер с удаленной отладкой (Chrome DevTools Protocol) для отладки веб-приложений.
/check-uuid
Check uuid
Проверь уникальность UUID в MDO-файлах 1С по указанному пути (или текущему проекту).
/docx-to-md
Docx to md
Конвертируй DOCX-файл в Markdown.
/move-project
Move project
Перенеси проект в другую папку, сохранив память, сессии и планы Claude Code.
/accept
Accept
Command dispatcher for accept.
/apply
Apply
Command dispatcher for apply.
/brainstorm
Brainstorm
Command dispatcher for brainstorm.
/change
Change
Command dispatcher for change.
/define
Define
Command dispatcher for define.
/design
Design
Command dispatcher for design.
/discover
Discover
Command dispatcher for discover.
/plan
Plan
Command dispatcher for plan.
/propose
Propose
Command dispatcher for propose.
/review
Review
Command dispatcher for review.
/tool
Tool
Command dispatcher for tool.
/browser-cdp
Browser cdp
浏览器操控。通过 CDP 协议控制 Chrome,复用已有登录态,执行浏览器自动化操作。
Make any song you can imagine
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