Train Mixture of Experts (MoE) models using DeepSpeed or HuggingFace. Use when training large-scale models with limited compute (5× cost reduction vs dense mode
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CLI tool for configuring and monitoring Claude Code
2048 above the Claude Code prompt: slide and merge tiles up to 2048. Plays while Claude works, pauses when the turn ends, keeps your best score; zero tokens. A single game split out of cc-arcade (MIT, Seza Akgün). Needs function hooks (early access) and an interactive terminal with a mouse.
Claude Code
Organization control mod: withholds the http and process nouns from $ so no plugin beneath it can reach the network or spawn processes, refuses user-tier plugins by name allowlist or by the $ calls their source declares, and withholds the Bash tool (shellPolicy "deny", default) or, in "guardrail" mode, denies well-known network clients as a bypassable speed bump. Hooks engine.create, plugin.register and tool.call; seat it in the managed prepend tier.
Claude Code
A side pane that draws the session's agent flow live: the main loop's context window, every subagent it spawns as a tree, and for each one the context handed down (its prompt, or the whole parent context for a fork), what it did with it (steps, tools, context size) and the answer it handed back up. Docked beside the transcript in the fullscreen layout, above the prompt otherwise. Needs function hooks (early access).
Claude Code
/aitmpl opens a component browser above the prompt: the aitmpl.com catalog (agents, commands, MCPs, settings, hooks, skills, loops, mods) read live from the site's public JSON through $.http.fetch. Pick a type or a trending component, filter, page, open a component and install it from there ($.process.run with the fixed CLI argv and a validated path, no shell), drop its install command into the prompt, or open its page in your browser. Hooks session.start, command.run and ui.render on AbovePromp
Claude Code
共 33 个插件包,通过下方列表选择查看。
共 914 项匹配内容,示例会单独标注;未声明归属的内容不代表插件自动包含。
Train Mixture of Experts (MoE) models using DeepSpeed or HuggingFace. Use when training large-scale models with limited compute (5× cost reduction vs dense mode
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Molecular featurization for ML (100+ featurizers). ECFP, MACCS, descriptors, pretrained models (ChemBERTa), convert SMILES to features, for QSAR and molecular M
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Expert in monorepo architecture, build systems, and dependency management at scale. Masters Nx, Turborepo, Bazel, and Lerna for efficient multi-project developm
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Create custom external web service APIs for Moodle LMS. Use when implementing web services for course management, user tracking, quiz operations, or custom plug
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Complete production-ready guide for Motion Canvas with ESM/CommonJS workarounds, full setup templates, and troubleshooting for programmatic video creation using
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Analyzes Move language packages against the official Move Book Code Quality Checklist. Use this skill when reviewing Move code, checking Move 2024 Edition compl
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Material-UI v7 component library patterns including sx prop styling, theme integration, responsive design, and MUI-specific hooks. Use when working with MUI com
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Multiplayer game development principles. Architecture, networking, synchronization.
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Write JavaScript code in n8n Code nodes. Use when writing JavaScript in n8n, using $input/$json/$node syntax, making HTTP requests with $helpers, working with d
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Write Python code in n8n Code nodes. Use when writing Python in n8n, using _input/_json/_node syntax, working with standard library, or need to understand Pytho
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Validate n8n expression syntax and fix common errors. Use when writing n8n expressions, using {{}} syntax, accessing $json/$node variables, troubleshooting expr
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Expert guide for using n8n-mcp MCP tools effectively. Use when searching for nodes, validating configurations, accessing templates, managing workflows, or using
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Operation-aware node configuration guidance. Use when configuring nodes, understanding property dependencies, determining required fields, choosing between get_
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Interpret validation errors and guide fixing them. Use when encountering validation errors, validation warnings, false positives, operator structure issues, or
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Proven architectural patterns for building n8n workflows.
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Proven workflow architectural patterns from real n8n workflows. Use when building new workflows, designing workflow structure, choosing workflow patterns, plann
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Suggest better variable, function, and class names based on context and conventions.
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Educational GPT implementation in ~300 lines. Reproduces GPT-2 (124M) on OpenWebText. Clean, hackable code for learning transformers. By Andrej Karpathy. Perfec
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GPU-accelerated data curation for LLM training. Supports text/image/video/audio. Features fuzzy deduplication (16× faster), quality filtering (30+ heuristics),
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Evaluates LLMs across 100+ benchmarks from 18+ harnesses (MMLU, HumanEval, GSM8K, safety, VLM) with multi-backend execution. Use when needing scalable evaluatio
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NVIDIA's runtime safety framework for LLM applications. Features jailbreak detection, input/output validation, fact-checking, hallucination detection, PII filte
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Instantly provision production-ready Postgres databases with Neon Instagres. Use when setting up databases, when users mention PostgreSQL/Postgres, database set
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Expert patterns for Neon serverless Postgres, branching, connection pooling, and Prisma/Drizzle integration Use when: neon database, serverless postgres, databa
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Nest.js framework expert specializing in module architecture, dependency injection, middleware, guards, interceptors, testing with Jest/Supertest, TypeORM/Mongo
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