LLM Mart Basic

Drop a specific skill version or an entire skill — soft (deprecate) or hard (purge) with platform context rebuild. Use when the user requests to "drop" or "remove a skill."

Pre-code stack feasibility verification against architecture and PRD documents. Use when the user requests to "verify a tech stack" or "verify stack."

Improve architecture doc using verified skill data and VS feasibility findings. Use when the user requests to "refine skill architecture" or "improve architecture doc."

Campaign orchestration — multi-library skill production with dependency tracking, file-based state, and resume. Use when the user asks to "run a campaign" or "orchestrate skills."

관계형 스키마를 설계·검토하거나 인덱스·쿼리 튜닝·트랜잭션·마이그레이션을 다룰 때, 그리고 doksam pig 의 공유 PostgreSQL 클러스터를 운영할 때 사용한다. SQLite 고유 주제는 sqlite-expert 를 쓴다.

doksam 프로젝트의 UI 를 만들거나 수정할 때, 사용자가 "ui.doksam.com 참고" / "doksam-ui" / "독삼 표준 UI" 라고 말할 때, 프론트엔드 작업이 doksam 인프라를 대상으로 할 때 사용한다. ui.doksam.com 을 디자인 단일 진실원천(SSOT)으로 강제한다 — shadcn/ui 시맨틱 토큰(색상 하드코딩 금지), 브랜드 프로필, 자체 호스팅 shadcn 커스텀 레지스트리(npx shadcn add https://ui.doksam.com/r/<name>.j

FinGuard CLI로 소스코드 취약점을 점검하고 심각도 기반 보안 게이트와 제한된 수정·재검증 루프를 수행할 때 사용한다. 일반 코드 품질 리뷰나 SCA·모의해킹은 범위 밖이다.

pnpm 워크스페이스와 Vite 빌드를 설정·정비하거나, 의존성·락파일·번들 크기·폐쇄망 self-host 문제를 다룰 때 사용한다. 프레임워크 자체의 코드 작성이 아니라 빌드/패키징 층이 대상이다.

Go 코드를 작성·리뷰·리팩터링하거나 에러 처리, 동시성, 테스트, net/http 서버, go:embed 를 다룰 때 사용한다. Go 1.22+ 기준.

세션을 끊고 다음 세션에 넘긴다 — 협업 인프라(GitHub·GitLab·Forgejo·Jira·Plane·Slack)가 있으면 재개 가능한 상태를 그 트래커 이슈 본문으로 남기고 HANDOFF.md 에는 이슈 URL 을 가리키는 포인터만 적어 URL 하나로 건네고, 없으면 HANDOFF.md 자체에 전체 내용을 적어 그 파일로 끝낸다. 작업 이슈를 닫은 경계에서는 전용 이슈 대신 다음 작업 이슈에 코멘트 하나로 남긴다. 넘겨받은 쪽은 포인터나 파일을 읽고 적힌 단언을 실제와 대조한 뒤 이어서 착

에이전트 영속 메모리를 실제 근거(코드·DB·이슈 트래커·파일시스템)와 대조해 낡은 기억을 교정하고 죽은 기억을 아카이브 후보로 보고하는 감사 스킬. 메모리가 ~30개 파일을 넘었을 때, 큰 스택/인프라 변경(라이브러리 교체, 버전 업그레이드, 서버 이전, 스키마 삭제) 직후, 두 메모리가 서로 모순돼 보일 때, 또는 "메모리 정리해줘 / 감사해줘"(clean up / audit my memory) 요청에 사용한다.

사용자가 모바일 웹/앱의 기획서 / 화면설계서 / 스토리보드(storyboard) / 와이어프레임(wireframe) / IA / 화면기획을 요청할 때 도메인 불문(쇼핑, 커뮤니티, 예약, 뉴스, O2O, ...) 사용한다. PPT 스타일 16:9 슬라이드로 구성된 자체 완결형 HTML 파일 하나와, 화면 ID 를 키로 하는 Business Rules 마크다운 명세(검증·인터랙션·엣지케이스)를 산출한다.

mobile-web-planner의 Storyboard와 Business Rules를 동작하는 웹앱으로 구현할 때 사용한다. 프론트는 Next.js App Router 또는 Vite + React SPA 중 선택하고 화면·규칙 ID 추적표, 빌드, 핵심 User Flow 검증까지 완료한다. 기획 문서 없는 일반 React 컴포넌트 작업은 react-expert, Vite 설정만 다루는 작업은 frontend-build를 쓴다.

React 컴포넌트를 설계·구현·리팩터링하거나 상태 관리, useEffect 남용, 리렌더 성능, 접근성 문제를 다룰 때 사용한다. React 19 기준.

사용자가 "홈페이지 만들어줘" 등 단일 요청으로 서비스 전체 제작을 원할 때 기획(mobile-web-planner), 구현(nextjs-implementer), 보안(finguard)을 순차적으로 위임하고 통제하는 총괄 PM 메타 스킬. 스킬 룰 개정이나 진화는 skill-evolve 에 맡긴다.

사용자가 "녹음시작" / "녹음 시작" / "강의 녹음" / "회의 녹음" / "전사 시작" 이라고 하거나, 실시간 강의·회의·교육 세션의 녹음과 요약을 요청할 때 사용한다. 실시간 전사와 함께 오디오 원본(m4a)도 저장한다. 실행을 멈추는 "녹음종료" / "녹음 끝" 도 이 스킬이 처리한다.

피드백 기반으로 SKILL.md를 자동 개선하는 메타 스킬

SQLite 파일을 직접 읽고 쓰거나, 읽기 전용 조회·WAL·잠금·마이그레이션·동적 테이블명 주입 같은 SQLite 고유 문제를 다룰 때 사용한다.

用户明确说“规格已确认，开始实现”或要求按已审批 CM specs 开发时使用。新任务默认由 JS workflow 驱动 N1-N8，完成开发、独立审查、QA 与文档同步；模糊点子、未审规格和单独一句“继续”不能触发编码批准。

后端 API 工程师 Skill，执行服务端 API 层开发（路由、业务逻辑、鉴权中间件、缓存、队列），自动适配语言和框架

Every VM came back. The cluster did not. Declarative systems converge on config, and the datapath isn't config.

A surprising share of AI-in-the-terminal failures aren't the AI. They're zsh, and a version of bash from 2006.

A Claude Code plugin turns standalone project configuration into a namespaced, installable extension that teams and communities can update as one unit.

None of the safety came from the model. It came from six boring habits.

Skills package instructions and references. Subagents run work in a separate context and return results. They solve different problems and can be composed deliberately.

Six hours in, one step left, everything green, and the incident that didn't happen

CLAUDE.md carries persistent project context. Skills load reusable procedures when relevant. Separating stable facts from task-specific workflows keeps both easier to maintain.

Twenty minutes recovering secrets that never existed, and the one sentence from a human that ended it

An API request routing a model's tool call through an approval gate to a remote MCP server

31 config keys, two audits, and why the first one was wrong in both directions

The official MCP Registry stores standardized server metadata rather than package code. Publishers verify a namespace, describe installation or remote access, and submit immutable versions.

Everyone looks at the Dockerfile. The file that actually leaked the key was the project file.

Remote MCP authorization uses established OAuth standards, but secure integration still requires issuer validation, least-privilege scopes, protected token handling, and server-side enforcement.

"Copy it over and switch the reference" is two steps, and the outage lives in the one nobody checks

stdio fits local processes and prototypes. Streamable HTTP fits hosted services and shared integrations. The right choice follows where the capability runs and who must reach it.

The most important rule wasn't about what I could change. It was about what I was allowed to display.

Tools perform operations, resources expose readable context, and prompts provide reusable templates. Choosing the correct primitive makes an MCP server easier to understand and govern.

Use MCP Inspector to connect to local or remote servers, inspect capabilities, call tools, read resources, test prompts, and diagnose failures before release.

Build an MCP server in TypeScript with focused tools, validated schemas, local and remote transports, Inspector tests, and production security controls.

An MCP server exposes tools, resources, or prompts through a standard protocol so an AI application can discover and use external capabilities.

Periodic multi-reviewer sweep of the whole codebase — surfaces a triaged checkpoint report.

Sanctioned lane for non-behavioral work — docs-only edits, dependency bumps, reverts. Type-scaled gates; no TDD demanded of prose.

{{SKILL_ENTRY:post-merge-cleanup}}

Show the codeArbiter command catalog — the public command list and what each routes to.

{{SKILL_ENTRY:commit-gate}}

Stop everything and surface a rule conflict — persona vs. docs vs. code. Present both sides and the conflict-hierarchy level; the user resolves. No silent reconciliation.

{{SKILL_ENTRY:context-check}}

{{SKILL_ENTRY:context-creation}}

{{SKILL_ENTRY:debug}}

{{SKILL_ENTRY:decompose}}

Verify the active host install, package, command ownership, enforcement{{IF:pi}}, wrapper self-test, and active-dispatch coverage gap{{ELSE}}, and harmless live-fire probe{{END}}. Read-only.

Start a feature: brainstorm a spec, get it approved, then drive it test-first through the pipeline. The one entry to implementation.

Fix a confirmed bug: a failing regression test first, then a minimal fix, then the rest of the tdd gates.

Opt this repo into codeArbiter — scaffold the root-level .codearbiter/ state store.

Read-only 3-metric governance glance — override rate, small-lane rate, sprint low-confidence ratio — each with a trend arrow vs. the prior 20-commit window.

Sanctioned, logged bypass of a gate or hard rule — one audit line, then proceed.

{{SKILL_ENTRY:finishing-a-development-branch}}

Zero-onboarding, read-only dry-run of the reviewer fleet against the current uncommitted diff. Predicts reviewers, runs the state-free secret scan, writes nothing.

Trim transcript clutter to extend session lifetime — analyze, prune a copy, or toggle the after-each-turn service. Dry-run by default; gains land at resume/compaction, not the current turn.

{{SKILL_ENTRY:decision-variance}}

Your car as a chat-room agent: Raspberry Pi 5 + dashcam + local AI. CodeWatch's sibling for the garage.

The enterprise gateway for autonomous agents. Identity management, per-channel isolation, credential vault, per-session tamper-evident audit log.

AI agent for Home Assistant — talk to your home, create automations in plain language, analyze cameras with face recognition, and get proactive anomaly alerts.…

A desktop app to prototype agent ideas, inspect every harness step, replay failures, and evaluate performance, all in one place. Local-first, cloud-ready for ma…

Local-first AI memory you can see, edit, and override — portable across Claude Code, Codex, Cursor, Windsurf, and other MCP coding tools.

Web & desktop (Electron) client for the OCTO open workplace — one React + TypeScript codebase shipping browser and PC surfaces, with first-class AI agent UX.

同花顺官方 A股金融数据服务，提供股票实时行情、历史行情、财务报表、指数、板块、涨停等数据，适用于 AI Agent、量化研究和应用开发，支持 API、MCP、CLI 和 Python。Official Tonghuashun (HiThink) A-share financial data service provi…

Open-source desktop SQL workspace for PostgreSQL, MySQL/MariaDB, SQLite and 15+ more databases like DuckDB, ClickHouse, Redis and Firestore. Built-in MCP server…

🤖 Local-assist BOSS Zhipin CLI for AI agents — search, welfare filtering, shortlist, JSON-envelope output; low-risk & compliant by default.

The local-first sidebar AI agent for ComfyUI — runs on your own Claude OR ChatGPT subscription (no API keys, no extra LLM costs). Drives your live graph: edits,…

Persistent memory for Claude Code — identity, context, and continuity across sessions

🔬 A curated collection of 23,000+ agent skills for empirical research across 8 social science disciplines. | 精选 23,000+ AI Agent 技能库，覆盖8大社会科学学科的实证研究。CoPaper.AI…

A curated list of plugins, skills, MCP servers, patch/profile layers, orchestrators & UIs for DeepSeek Harness (DSH). Visualization · PPT · Coding · Agents · Lo…

World Memory Protocol.

Run your own organization of agents.

The most RAM efficient harness

AI-native, free, open-source alternative to Jira, Trello, ClickUp & Monday. Built for Scrum teams where humans and AI agents collaborate as equals — on the same…

Free open-source desktop app that scrapes JAV metadata and generates NFO + cover art for Jellyfin, Emby & Kodi. No Docker, no CLI — one-click install on Windows…

A cross-platform desktop app to manage Agent Skills in one place and sync them to multiple AI coding tools’ global skills directories — “Install once, sync ever…

天枢 (Tianshu) 是一个基于harness工程的终端编程智能体运行时（Tui X Gui），针对DeepSeek V4 做了前缀缓存工程优化（长会话实测稳态命中率 97–99%）和深度适配。它跳出了传统 AI 编程助手把大模型仅当成“工具”的局限，基于认知虚拟机 (CVM)、自感知层和信息素（Stigmergy…