Claude Code 플러그인
공개 Claude Code 마켓플레이스의 플러그인 151개입니다. 각 플러그인은 함께 설치되는 스킬, 슬래시 명령, 에이전트, 훅 또는 MCP 서버를 묶습니다.
필터와 일치하는 151개의 플러그인을 표시합니다.
공개 Claude Code 마켓플레이스의 플러그인 151개입니다. 각 플러그인은 함께 설치되는 스킬, 슬래시 명령, 에이전트, 훅 또는 MCP 서버를 묶습니다.
필터와 일치하는 151개의 플러그인을 표시합니다.
.claude-plugin/marketplace.json이 포함된 repo를 제출하면 모든 plugin을 목록에 추가합니다.
marketplace 제출LLM application development with LangGraph, RAG systems, vector search, and AI agent architectures for Claude 4.6 and GPT-5.4
Eval-gated LLM fine-tuning lifecycle (LoRA/QLoRA, DPO, GRPO/RLVR, vision SFT, quantized export). Use when fine-tuning an open-weights model end-to-end: building the eval harness first, selecting method and model, preparing data, training with Unsloth or TRL, gating checkpoints, and exporting GGUF/FP8.
Multi-agent collaboration — spawn N parallel subagents that compete on code optimization, content drafts, research approaches, or any task that benefits from diverse solutions. 7 slash commands (/hub-init, /agenthub:spawn, /hub-status, /agenthub:eval, /agenthub:merge, /agenthub:board, /hub-run), agent templates, DAG-based orchestration, LLM judge mode, message board coordination.
A second brain for Claude Code + Obsidian inspired by Karpathy's LLM Wiki gist. Turn any LLM CLI into a disciplined wiki maintainer: incrementally ingest sources into a persistent, interlinked markdown vault; update entity/concept/source pages; flag contradictions; maintain index and append-only log. Knowledge compounds instead of being re-derived by RAG on every query. Ships 3 sub-agents (wiki-ingestor, wiki-librarian, wiki-linter), 5 slash commands (/wiki-init, /wiki-ingest, /wiki-query, /wiki-lint, /wiki-log), 8 Python tools (stdlib only: init_vault, ingest_source, update_index, append_log, wiki_search BM25, lint_wiki, graph_analyzer, export_marp), 8 reference docs, full vault templates (CLAUDE.md, AGENTS.md, cursorrules, 5 page templates), and a worked example vault. Cross-tool compatible with Claude Code, Codex CLI, Cursor, Antigravity, OpenCode, and Gemini CLI.
Complete OpenRouter integration skill pack with 30 skills covering LLM routing, model selection, cost optimization, and multi-provider orchestration. Flagship+ tier vendor pack.
Static lint for Claude Code plugins and skills, with experimental LLM scoring for skills
AI/ML engineering skills for shipping AI features responsibly: Model Card, AI Eval Plan, RAG Design Doc, Agent Spec, Dataset Datasheet, AI Feature PRD, LLM Cost & Latency Budget, Prompt Optimizer, Eval Rubric Designer, RAG Architecture Review, LLM Guardrails Spec, Agent Design Review, and Model Selection Advisor.
Operate AI agents and LLM features in production: prompt regression suites, model migration plans, context-engineering reviews, agent incident postmortems, and observability specs — plus the pm-ai evaluation and cost skills they build on.
Twelve ICLR-specific skills for ML conference submission strategy, grounded in official ICLR 2026 CFP, Author Guide, Reviewer Guide, Code of Ethics, Code of Conduct, and LLM-use policy.
academicTwelve ICML-specific skills for ML conference submission strategy, grounded in official ICML 2026 author instructions, CFP, Peer Review FAQ, review instructions, and LLM-review policy.
academicTools, skills, and CLI extensions for designing and productionizing LLM inference pipelines. Pattern-guided, slim by default, eval-first.
React, Vue, Svelte, CSS and component skills for building interfaces.
SQL, analytics, datasets, models and machine-learning workflows.
Docker, Kubernetes, CI/CD and cloud (AWS/Azure/GCP) automation.
For developers creating and maintaining skills for AI coding agents.
Create design tokens, principles, and naming conventions for a new design system.
Audit code changes for bugs, security flaws, and quality issues before merging.
Identify design debt, audit tokens, and enforce consistency across a product.
Install this pack to generate a complete brand identity kit including logo, color palette, typography, and mockups.
Analyze competitor ads, design ad creative, and set up campaigns on Google/Meta/LinkedIn.