LLM Mart Basic

Rename a skill across all its versions — transactional copy-verify-delete with platform context rebuild. Use when the user requests to "rename a skill."

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。

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.

Treat an AI agent skill as both an instruction package and a software dependency: inspect what it says, what it runs, what it can access, and how it updates.

Add remote HTTP or local stdio MCP servers to Claude Code, choose the right scope, protect credentials, verify the connection, and test with least privilege.

Find and execute an ImmyBot PowerShell script on a target computer (destructive, SYSTEM context)

Search the ImmyBot software catalog (per-tenant + global)

Portfolio-wide Inforcer baseline drift report — every managed tenant's alignment vs its assigned baseline, classified aligned / semi-aligned / drifted and sorted drifted-first, with secure score

Single-tenant Microsoft 365 posture snapshot from Inforcer — secure score plus alignment score, band, and the per-policy drift detail against the tenant's assigned baseline

Get an Ironscales AI verdict on a raw email, then act on it with a remediation action

Triage open Ironscales phishing incidents — list by status and severity, investigate, and remediate

Get a Kaseya Quote Manager quote with its sections and line items

Get a Kaseya Quote Manager sales order with its lines and payments

List Kaseya Quote Manager quotes, optionally scoped to a recent window

Add a note or comment to an existing Autotask ticket

View contract status, entitlements, and remaining hours for a company or specific contract

Check pricing details for an Autotask product or service from price lists

Create a new Autotask quote with line items for products, services, and service bundles

Create a new service ticket in Autotask PSA

Use this skill when working with Autotask expense reports - creating reports, adding expense items, searching by status or submitter, and tracking reimbursable and billable expenses

Search for Autotask configuration items/assets by name, serial number, or company

Search for Autotask companies by name, ID, or other attributes

Search for Autotask contacts by name, email, phone, or company

List tickets currently assigned to you with optional filtering

Reassign a ticket to a different resource or queue

An open-source, privacy-first, self-hosted knowledge workspace where humans and AI agents work together 开源、隐私优先、自托管的知识工作空间，让人与智能体在此协作

Scale computer-use 2.0 with open-source drivers, cross-OS fleets, and benchmarks for training, evaluation, and data generation.

The go-to web for your AI coding agent — local-first search, fetch, crawl & research over MCP. No API keys, no cloud, $0/query. Public beta.

Transform and optimize your markdown documentation for Large Language Models (LLMs) and RAG systems. Generate llms.txt automatically.

合乎周礼：DeepSeek-powered Zhouli-style Chinese translator, web app, and distributable Skill package.

This is a fork of the https://dockbox.dev project I made

🏆 Curated, ranked list of AI agent harnesses (100+) — plus an MCP server, llms.txt & JSON so agents can recommend them too. Rescored weekly.

A Python framework for modular, self-contained skill management for machines.

ADHD — a skill for coding agents. Tree-of-thought with pruning, built on the Claude & Codex Agent SDK. Fans out parallel divergent thoughts under different cogn…

AI Agent 驱动的开源可自部署视频工作台：将小说与剧本转为角色、场景、道具资产、分镜、视频和剪映草稿，支持跨镜头一致性、多供应商与费用追踪 | Self-hosted AI video workspace for stories, storyboards and short-form video producti…

DeepSeek Harness Desktop App: a local AI desktop workspace for DSH Sessions, projects, files, web research, plugins, and Office artifacts.

Autonomous Offensive Security, Bug Bounty & Red Teaming Agent Framework powered by Hermes Agent, specialized reasoning skills, and multi-model LLM orchestration…

⌥ Coding agent with the IDE wired in

Supercharge AI Agents, Safely

X (Twitter) Scraper API and X API Alternative. You do not need an official X developer account. You do not need to connect or use an X account for supported scr…

My AI Stand. Realtime by day, rewriting itself by night. Summon my AI superpower.

Open-source coding agent for your terminal, built in Rust and on a journey of continuous community improvement. Issues and PRs welcome.

观澜 / Guanlan：AI Agent 的中文互联网研究、阅读与信源路由工具。

Mac Agent for macOS 26: the agentic AI harness for your Mac Desktop. Computer use, automation, scripting, coding, and more. Powered by 18+ providers across loca…

Semantic version control => entity-level diffs, blame, and impact analysis on top of git. 28 languages via tree-sitter. Built for coding agents.