LLM Mart Basic

코드 변경사항 전체 리뷰. code-reviewer 에이전트 + security-audit 에이전트를 순차 실행하는 래퍼 스킬. PR/MR 생성 전 또는 리뷰 요청 시 사용.

코드를 새로 짜기 전에 기존 솔루션(레포 내부 → 사내 미러 → 패키지 레지스트리 → MCP/스킬 → GitHub)을 먼저 검색하는 워크플로. 새 기능/유틸/의존성 추가 직전, "X 기능 넣어줘" 요청에 코드부터 쓰려는 순간 발동. (원본: [affaan-m/ECC](https://github.com/affaan-m/ECC) 의 search-first 스킬, MIT — 이식·번안)

외부 보안팀 코드 검사 전 자체 사전점검. security-audit 에이전트(+ 설정돼 있으면 SonarQube 보안 핫스팟)를 돌려 P0/P1/P2로 정리하고, 발견사항을 이슈로 쪼개 병렬 서브에이전트로 고친다. "보안 검사", "보안 점검", "코드 감사" 언급 시 사용.

스킬 실행 후 피드백을 받아 해당 SKILL.md를 자동 개선하는 메타 스킬. 스킬이 틀렸거나 누락이 있을 때, 또는 새로 배운 함정을 기록할 때 사용.

프로젝트 상태 한눈에 보기. Git 상태·빌드·테스트·최근 이슈·브랜치 현황을 한 번에 조회. 작업 시작 전 또는 상태 점검 시 사용.

Bring documentation back in line with the code after changes to behavior, paths, versions, or generated output. Use on "update the docs", "refresh the README", "docs are stale", and right before opening a PR that changed any of those. Checks each documented claim against the actu

Duplicate this file to create a project skill. Write the trigger condition concretely in the description.

Use when the user invokes /grill-me or asks to have an idea, feature request, or spec grilled, stress-tested, interrogated, or challenged before implementation. Opt-in alternative to superpowers:brainstorming — the user picks one or the other per task.

Fact-check an agent's persistent memory against ground truth — verify each memory's load-bearing claims against code, database, issue tracker and filesystem, correct the stale ones, and report dead ones as archive candidates. Use when memory grows past ~30 files, right after a bi

Full review of code changes. A wrapper skill that runs the code-reviewer agent and the security-audit agent in sequence. Use before creating a PR/MR or when a review is requested.

A workflow that searches for an existing solution (this repo → internal mirrors → package registries → MCP/skills → GitHub) before writing new code. Triggers right before adding a new feature/utility/dependency, or the moment a "add feature X" request tempts you to jump straight

Self-run security pre-check ahead of an external security-team code audit. Runs the security-audit agent (plus SonarQube security hotspots when configured), grades findings P0/P1/P2, splits them into issues, and fixes them with parallel subagents. Use on "security check", "securi

A meta-skill that takes feedback after a skill runs and automatically improves the corresponding SKILL.md. Use when a skill was wrong or incomplete, or to record a newly discovered gotcha.

See project status at a glance. Checks Git status, build, tests, recent issues, and branch status all at once. Use before starting work or when checking on status.

Imported from leeyudok/agents-scaffold/.claude/agents/README.md.

다른 서브에이전트를 실제로 써본 후 피드백을 받아 해당 agents/*.md를 자동 개선하는 메타 에이전트. 에이전트가 틀렸거나, 결과가 부실하거나, description이 실제 동작과 안 맞을 때, 또는 새로 배운 함정을 기록할 때 호출.

머지 전 코드 변경을 버그·보안·품질 관점으로 리뷰. CRITICAL 발견 시 차단 권고.

DB 스키마 변경 안전성 검증. ALTER TABLE 전 위험도 평가·롤백 SQL 생성·FK 정합성 체크. 마이그레이션 파일 추가·수정 시 호출.

기획서/이슈 기준 최소 스코프 구현 전담. 테스트 작성·실행은 하지 않음(sdlc-tester 담당). /sdlc-cycle 커맨드의 개발 단계 서브에이전트.

이슈의 AC/TC 기준 테스트 코드 작성 전담. 구현 코드 수정·테스트 실행은 하지 않음(sdlc-verifier 담당). /sdlc-cycle 커맨드의 테스트 단계 서브에이전트.

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.

Skills teach Claude a repeatable method, connectors provide governed access to apps and live data, and plugins package related capabilities for installation and sharing.

Use an agent skill to package reusable know-how and workflow instructions. Use an MCP server when an agent needs live, governed access to external data or actions.

Custom commands and skills can both create a slash-invoked workflow in Claude Code. The important choice is how the workflow is discovered, shared, and permissioned.

A useful Claude skill solves one recurring engineering job, is easy to inspect, and saves more time than it creates in setup and review.

Claude skills can live in your Claude account, your local Claude Code setup, or a repository. Install them where the sessions that need them can load them.

Build a portable AI agent skill from one repeatable job: a precise description, concise instructions, focused resources, and tests that prove it works.

AI agent skills package instructions, scripts, references, and templates into portable folders an agent loads only when the task calls for them.

AI made publishing cheap, which is exactly the problem. What separates a page worth ranking from a competent summary of the first ten results.

A prompt that works once isn't a quality system. Five cases, an observable rubric, and a regression set will tell you whether a change helped.

One character of YAML, four pods that never started, and two safety nets I didn't know were holding. Every restart is an audit. Schedule them before they schedule you.

"Verify your work" isn't an instruction. It's a mood. Here's the version that's an instruction. Verify with a different mechanism than the one that made the claim.

A prompt that works once may still fail in production. A lightweight eval set gives you repeatable cases, a clear rubric, and a way to see whether a prompt change actually improved the workflow.

The best AI tool is not the one with the longest feature list. It is the one that solves a defined job reliably, fits the workflow, handles data appropriately, and remains useful after the novelty wears off.

Use AI to speed research without losing trust. Learn to find primary sources, verify claims, preserve uncertainty, and keep an auditable source trail.

Better prompts aren't magic wording. They're short briefs that hand the model a task, the context it can't infer, the limits, and a quality bar.

网文封面生成。分析书名题材，生成专业封面图。

网文去AI味。检测并清除文本中的AI写作痕迹，让文字回归自然。

逆向导入已有小说。将已写好的小说反向解析为标准项目目录结构。

长篇网文拆文。深度拆解爆款长篇小说的黄金三章、人设、爽点、节奏。

长篇网文扫榜。分析起点、番茄、晋江等平台排行数据，提炼市场趋势。

长篇网文写作。从大纲到正文，辅助长篇网络小说的创作。

多视角对抗式审查。使用多个 Agent 对作品进行多维度审稿。

网文写作环境部署与检查。部署 hooks、rules、agents、项目指令等基础设施；传入 check 只检查不改动。

短篇网文拆文。拆解爆款短篇的故事核、结构、情感线和反转设计。

短篇网文扫榜。分析知乎盐言、番茄短篇等平台热门数据。

短篇网文写作。辅助短篇小说创作，从构思到成稿。

网文工具箱路由入口。根据模糊意图自动分发到对应的写作、拆文或扫榜工具。

浏览器操控。通过 CDP 复用 Chrome 登录态执行浏览器自动化。

小说封面生成。根据书名、作者名和题材生成专业网文封面。

网文去 AI 味。检测并清理模板化、解释腔和过度工整表达。

逆向导入已有小说，将成稿或半成品解析为可续写项目。

长篇网文拆文，分析黄金三章、人设、爽点和长线节奏。

长篇网文扫榜，分析起点、番茄、晋江等平台趋势。

长篇网文写作，从选题、大纲到逐章正文和持续追踪。

多视角小说审查；ZCode 项目 agents 不可用时自动降级 solo。

Make any song you can imagine

Leading AI-powered video generation platform that specializes in creating hyper-realistic talking avatars

Hermes Agent is an open-source, self-improving autonomous AI agent developed by Nous Research

Kilo Code is a popular, open-source AI coding agent and "agentic engineering" platform designed to help developers build, refactor, and debug software faster

General-purpose agent in one static Go binary. ReAct loop, ACP server for IDEs, OpenAI-compatible REST API with embedded web UI, Telegram gateway, cron schedule…

Autonomous agent framework with structured memory, safety hooks, and loop management. Built by the agent that runs on it.

TSP自托管、零运维的 A 股「选股 + 监控 + 回测」量化工作台 | 基于 TickFlow 数据源 | LLM能力驱使策略定制+个股分析+复盘 | 自由接入第三方数据源与个性化扩展数据 | 个人开源 ,非TickFlow官方项目

Curated, verified Agent Skills powered by ModelStudio.

Run Claude Code, Codex, Antigravity, Cursor Agent and OpenCode as one runtime — persistent sessions, multi-agent councils, an OpenAI-compatible endpoint, an MCP…

pi had nothing (nothing), so I made something (something) — sorry mariozechner-senpai, I went ahead and lovingly soiled your pure pi for you. opinionated fork o…

A persistent workspace for development work that self-improves and continues beyond one session.

Open-source memory and context for user-aware agents: scoped memory, provenance, retrieval quality, correction, boundaries, evals, and MCP/HTTP access.

📚 A zero-dependency, git-backed micro-lesson library for AI Agents to asynchronously share and search verified debugging experience. Python stdlib only. | http…

Deterministic, local-first memory and guardrails for AI coding agents with no LLM in the hot path.

Deterministic spec-orchestration for local LLMs in the pi coding agent — drives prompts through refine→research→grill→compose→critique, with bundled web/docs/fe…

Native Safari browser automation for AI agents. 97 tools via AppleScript — zero overhead, keeps logins, runs silently in background. Drop-in alternative to Chro…

Agent OS: keep specialist agents in a hub, spin up a temporary orchestrator per task. Local-first, works with any model.

Git for agent memory. Branches, diffs, PRs, and rollback for what your agents know.

Multi-Provider AI Gateway - No personal logs by design. Model autodiscovery, Failover groups, High availability, Android companion app, and more - "Because we h…

Production-grade MCP server for MikroTik RouterOS with secure AI-native network automation.