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.

Fourteen posts of being wrong in production, compressed to checkboxes

Healthy nodes, a quiet network, 300 restarts in three days, and a latency budget measured in milliseconds

Discovery worked. Ping worked. Every TCP connection timed out, and later the tunnel only worked when someone had a terminal open.

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.

Daily standup: all 9 departments report on the current project in parallel

Identify skills injected where not needed, propose regex and description tightening

Draft X/Twitter announcement post (or thread) for the latest plugin release

Deep quality audit of all skills, agents, and commands for inconsistencies, gaps, duplication, and token waste

Analyze negative-signal sessions for a skill, identify failure patterns, propose and apply fixes

Eval all skills with sufficient data, rank by procedure-following score, identify candidates for optimization

Propose a skill revision and compare fresh executions under a frozen rubric

Prune stale entries from the whetstone sync decision log

Bump version, commit, push, mirror to ai-skills, and update local plugin

Run the SkillOpt process-skill optimizer (offline, local). Default prints the exact bare-terminal command (safe); --run executes it in-session (hardened + checkpointed).

Analyze reference repos and recommend skill/agent/command improvements based on cross-repo patterns

Triage all open PRs with parallel agents, label, group, and review one-by-one

Author a new skill from scratch with paired trigger fixtures and full validation. Use when adding a skill that has no upstream skills.sh source (discipline, meta, or internal-pattern skills).

Create Architecture Decision Records with format selection and lifecycle management

Score each of the 5 agent-native principles (parity, granularity, composability, emergent capability, improvement-over-time) against a codebase and report gaps

Explore requirements and approaches through collaborative dialogue before planning implementation

Create engaging changelogs for recent merges to main branch

Expand each section of a plan via parallel research agents that add framework specifics, library conventions, and concrete implementation steps

Post-ship documentation sync. Reads all project docs, cross-references the diff, updates README/ARCHITECTURE/CONTRIBUTING/CLAUDE.md to match what shipped, polishes CHANGELOG voice, and optionally bumps the version.

Record a video walkthrough of a feature and add it to the PR description

Conduit — native SwiftUI iOS client for Hermes Agent

一个现代化的可视化规则引擎平台，用于编排复杂的 AI 工作流。在无限画布上设计、测试和部署 AI 流程——无需编写代码。结合 flowgram.ai 的能力与 Java 服务端，提供生产级工作流管理。在此之上提供AI Agent / Copilot的助手编排能力。

Job application tracker and AI-powered job search assistant. Helps job seekers manage their search journey with AI resume review, job matching, task logging, an…

📝 Markdown and HTML renderer for Svelte 5 — built for streaming AI agent output from Claude Code, ChatGPT, and agentic workflows. XSS-safe defaults, token cach…

ServiceNow MCP server: 500+ tools and 26 AI capabilities for any AI (Claude, ChatGPT, Gemini, Cursor, Copilot). Multi-transport (stdio, SSE, HTTP), A2A, dynamic…

Free crypto news API - real-time aggregator for Bitcoin, Ethereum, DeFi, Solana & altcoins. No API key required. RSS/Atom feeds, JSON REST API, historical archi…

Build production-ready AI agents in both Python and Typescript.

From agent user to agent builder: build a Claude Code-style coding agent from scratch in Python: 8 articles, 4 videos, one codebase

🪁 A lightweight, modern Kubernetes dashboard that unifies multi-cluster and resource management, enterprise-grade user governance (OAuth, RBAC, and audit logs)…

Stateful runtime management for LLM agents—inject, manipulate, and retrieve Python objects across turns.

AgentCall lets AI Agents join meetings with voice, video & screen-share to build together. Supports Google Meet, Teams, Zoom (Beta)

Kition brings Markdown, DataTable, WhiteBoard, a tool-using AI agent, browser research, and visual workflows into one desktop workspace.

IntentKit is an open-source, self-hosted cloud agent cluster that manages a collaborative team of AI agents for you.

A powerful Model Context Protocol (MCP) server providing comprehensive Google Maps API integration with LLM processing capabilities.

Turn your Claude Pro/Max subscription into an OpenAI-compatible API for your IDEs and devices — LAN auth, per-key quotas, response cache, disciplined cli.js ali…

Paw Work - selection-first web agent for Chrome: select on the live page, describe the outcome, take away an editable office file. BYOK, sandboxed, no server.

基于 AI Agent + MCP 工具链 + 渗透 Skill 编排， 配合大语言模型， 自然语言输入 → 自动完成「信息收集 → 漏洞发现 → 漏洞利用 → 报告生成」全流程。

Lexora — Personal AI workspace built around Desktop / 以 Desktop 为核心的个人 AI 工作台

First AI Journey for DevOps - with comprehensive learning paths, practical tips, and enterprise guidelines

AI coding agent with one Python core and three front-ends — headless CLI, Textual TUI, and an Electron desktop. Works with any OpenAI-compatible API, with risk-…