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MCP；它是管理 RunPod 的统一接口。",{"category":40,"check":133,"severity":42,"summary":134},"Overlapping near-synonym tools","该技能不公开多个近乎同义的工具；它协调一个单一的工作流程。",{"category":45,"check":136,"severity":24,"summary":137},"Phantom features","README 中提到的所有功能，如 RunPod 设置和管理，都在 SKILL.md 和提供的脚本中具有相应的实现或详细文档。",{"category":139,"check":140,"severity":24,"summary":141},"Install","Installation instruction","README 提供了清晰、可复制的 Python 依赖项安装说明，以及有关为 RunPod API 密钥设置环境变量的指南。",{"category":143,"check":144,"severity":24,"summary":145},"Errors","Actionable error messages","SKILL.md 包含一个故障排除部分，其中概述了常见错误、其症状和补救步骤，提供了可操作的指导。",{"category":147,"check":148,"severity":24,"summary":149},"Execution","Pinned dependencies","tools/requirements.txt 文件固定了 Python 依赖项，并且 README 建议通过 pip 安装它们，从而确保了可重复的环境。",{"category":33,"check":151,"severity":42,"summary":152},"Dry-run preview","该技能的主要功能涉及设置和 API 交互，而不是直接的状态更改操作，这些操作会受益于预演预览。",{"category":154,"check":155,"severity":24,"summary":156},"Protocol","Idempotent retry & timeouts","文档隐式建议重试 API 调用并提到处理作业状态轮询，表明考虑了操作稳定性。",{"category":117,"check":158,"severity":24,"summary":159},"Telemetry opt-in","没有迹象表明此技能会收集遥测数据；所有操作都是本地配置和 API 交互。",{"category":40,"check":161,"severity":24,"summary":162},"Precise Purpose","该技能的目的精确定义为通过 RunPod serverless 管理云 GPU 处理，并为设置、部署、资源管理和故障排除提供了明确的触发器。",{"category":40,"check":164,"severity":24,"summary":165},"Concise Frontmatter","SKILL.md 中的前言简洁明了，并在字符限制内有效地总结了该技能的核心能力和使用场景。",{"category":45,"check":167,"severity":24,"summary":168},"Concise Body","SKILL.md 结构良好，避免了不必要的冗长，将详细的 API 参考委托给特定部分。",{"category":170,"check":171,"severity":24,"summary":172},"Context","Progressive Disclosure","SKILL.md 中的特定部分提供了详细的 API 参考，符合渐进披露原则。",{"category":170,"check":174,"severity":42,"summary":175},"Forked exploration","此技能专注于管理和设置，而不是深入探索或代码审查，因此“上下文：分支”不适用。",{"category":22,"check":177,"severity":24,"summary":178},"Usage examples","SKILL.md 包含清晰的设置和部署命令行示例，并描述了预期的结果。",{"category":22,"check":180,"severity":24,"summary":181},"Edge cases","SKILL.md 中的故障排除部分解决了常见问题，如冷启动缓慢、OOM 错误和工作程序可用性，并提供了记录的恢复步骤。",{"category":104,"check":183,"severity":42,"summary":184},"Tool Fallback","此技能不依赖需要回退的外部工具；它直接与 RunPod API 交互。",{"category":186,"check":187,"severity":24,"summary":188},"Safety","Halt on unexpected state","设置过程意味着一个结构化的工作流程，并且故障排除部分表明失败将导致进程停止，从而提示用户进行干预。",{"category":92,"check":190,"severity":24,"summary":191},"Cross-skill coupling","此技能独立运行，并且不隐式依赖于在同一会话中加载的其他技能。",1778686491172,"此技能提供了一个与 RunPod serverless 交互的全面接口，使用户能够设置、部署 Docker 映像、管理 GPU 资源并了解成本。它涵盖了五个特定工具包映像的设置和管理，包括详细的 API 参考和故障排除指南。",[195,196,197,198,199],"设置和部署 RunPod 端点","管理 GPU 资源和 Docker 映像","排查端点问题","详细的 RunPod API 参考（GraphQL 和 REST）","成本了解和优化指南",[201,202,203,204],"直接在本地运行 AI 模型","管理本地计算机硬件","提供通用的云管理工具","取代 RunPod Web 控制台的所有任务",[],[207,208,209],"RunPod 帐户和 API 密钥","Cloudflare R2 凭证（可选，用于文件传输回退）","建议使用 Python 3.9+","3.0.0","4.4.0","使用户能够通过 RunPod serverless 利用云 GPU 处理能力，从而高效地部署和管理 AI 模型和 Docker 映像。","该技能在文档、安全性和生产就绪性方面表现出色，所有检查均通过或不适用。广泛的文档和清晰的设置说明有助于获得高分。",98,"通过 RunPod 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music generation with ACE-Step 1.5 — background music, vocal tracks, covers, stem extraction, audio repainting, and continuation for video production. Use when generating music, soundtracks, jingles, or working with audio stems. Triggers include background music, soundtrack, jingle, music generation, stem extraction, cover, style transfer, repaint, continuation, or musical composition tasks.","acestep",{"claudeCode":12},"SKILL.md frontmatter at .claude/skills/acestep/SKILL.md",[284],{"path":285,"priority":286},"SKILL.md","mandatory","rule","en",{"basePath":290,"description":291,"displayName":292,"installMethods":293,"rationale":294,"selectedPaths":295,"source":287,"sourceLanguage":288,"type":260},".claude/skills/elevenlabs","Generate AI voiceovers, sound effects, and music using ElevenLabs APIs. Use when creating audio content for videos, podcasts, or games. Triggers include generating voiceovers, narration, dialogue, sound effects from descriptions, background music, soundtrack generation, voice cloning, or any audio synthesis task.","elevenlabs",{"claudeCode":12},"SKILL.md frontmatter at .claude/skills/elevenlabs/SKILL.md",[296,297],{"path":285,"priority":286},{"path":298,"priority":299},"reference.md","medium",{"basePath":301,"description":302,"displayName":303,"installMethods":304,"rationale":305,"selectedPaths":306,"source":287,"sourceLanguage":288,"type":260},".claude/skills/ffmpeg","Video and audio processing with FFmpeg. Use for format conversion, resizing, compression, audio extraction, and preparing assets for Remotion. Triggers include converting GIF to MP4, resizing video, extracting audio, compressing files, or any media transformation task.","ffmpeg",{"claudeCode":12},"SKILL.md frontmatter at .claude/skills/ffmpeg/SKILL.md",[307,308],{"path":285,"priority":286},{"path":298,"priority":299},{"basePath":310,"description":311,"displayName":312,"installMethods":313,"rationale":314,"selectedPaths":315,"source":287,"sourceLanguage":288,"type":260},".claude/skills/frontend-design","Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, or applications. Generates creative, polished code that avoids generic AI aesthetics.","frontend-design",{"claudeCode":12},"SKILL.md frontmatter at .claude/skills/frontend-design/SKILL.md",[316],{"path":285,"priority":286},{"basePath":318,"description":319,"displayName":320,"installMethods":321,"rationale":322,"selectedPaths":323,"source":287,"sourceLanguage":288,"type":260},".claude/skills/ltx2","AI video generation with LTX-2.3 22B — text-to-video, image-to-video clips for video production. Use when generating video clips, animating images, creating b-roll, animated backgrounds, or motion content. Triggers include video generation, animate image, b-roll, motion, video clip, text-to-video, image-to-video.","ltx2",{"claudeCode":12},"SKILL.md frontmatter at .claude/skills/ltx2/SKILL.md",[324],{"path":285,"priority":286},{"basePath":326,"description":327,"displayName":328,"installMethods":329,"rationale":330,"selectedPaths":331,"source":287,"sourceLanguage":288,"type":260},".claude/skills/moviepy","Python video composition with moviepy 2.x — overlaying deterministic text on AI-generated video (LTX-2, SadTalker), compositing clips, single-file build.py video projects. Use when adding labels/captions/lower-thirds to LTX-2 or SadTalker outputs, building short ad-style spots in pure Python without Remotion, or doing programmatic video composition. Triggers include text overlay on video, label LTX-2 clip, caption SadTalker output, lower third, build.py video, moviepy, Python video composition, sub-30s ad spot.","moviepy",{"claudeCode":12},"SKILL.md frontmatter at .claude/skills/moviepy/SKILL.md",[332],{"path":285,"priority":286},{"basePath":334,"description":335,"displayName":336,"installMethods":337,"rationale":338,"selectedPaths":339,"source":287,"sourceLanguage":288,"type":260},".claude/skills/playwright-recording","Record browser interactions as video using Playwright. Use for capturing demo videos, app walkthroughs, and UI flows for Remotion videos. Triggers include recording a demo, capturing browser video, screen recording a website, or creating walkthrough footage.","playwright-recording",{"claudeCode":12},"SKILL.md frontmatter at .claude/skills/playwright-recording/SKILL.md",[340,341],{"path":285,"priority":286},{"path":298,"priority":299},{"basePath":343,"description":344,"displayName":345,"installMethods":346,"rationale":347,"selectedPaths":348,"source":287,"sourceLanguage":288,"type":260},".claude/skills/qwen-edit","AI image editing prompting patterns for Qwen-Image-Edit. Use when editing photos while preserving identity, reframing cropped images, changing clothing or accessories, adjusting poses, applying style transfers, or character transformations. Provides prompt patterns, parameter tuning, and examples.","qwen-edit",{"claudeCode":12},"SKILL.md frontmatter at .claude/skills/qwen-edit/SKILL.md",[349,350,352,354],{"path":285,"priority":286},{"path":351,"priority":299},"examples.md",{"path":353,"priority":299},"parameters.md",{"path":355,"priority":299},"prompting.md",{"basePath":357,"description":358,"displayName":359,"installMethods":360,"rationale":361,"selectedPaths":362,"source":287,"sourceLanguage":288,"type":260},".claude/skills/remotion","Toolkit-specific Remotion patterns — custom transitions, shared components, and project conventions. For core Remotion framework knowledge (hooks, animations, rendering, etc.), see the `remotion-official` skill.","remotion",{"claudeCode":12},"SKILL.md frontmatter at .claude/skills/remotion/SKILL.md",[363,364],{"path":285,"priority":286},{"path":298,"priority":299},{"basePath":366,"description":367,"displayName":368,"installMethods":369,"rationale":370,"selectedPaths":371,"source":287,"sourceLanguage":288,"type":260},".claude/skills/remotion-official","Best practices for Remotion - Video creation in React","remotion-best-practices",{"claudeCode":12},"SKILL.md frontmatter at .claude/skills/remotion-official/SKILL.md",[372],{"path":285,"priority":286},{"basePath":257,"description":374,"displayName":219,"installMethods":375,"rationale":376,"selectedPaths":377,"source":287,"sourceLanguage":288,"type":260},"Cloud GPU processing via RunPod serverless. Use when setting up RunPod endpoints, deploying Docker images, managing GPU resources, troubleshooting endpoint issues, or understanding costs. Covers all 5 toolkit images (qwen-edit, realesrgan, propainter, sadtalker, qwen3-tts).",{"claudeCode":12},"SKILL.md frontmatter at .claude/skills/runpod/SKILL.md",[378],{"path":285,"priority":286},{"basePath":380,"description":381,"displayName":382,"installMethods":383,"rationale":384,"selectedPaths":385,"source":287,"sourceLanguage":288,"type":260},"skills/openclaw-video-toolkit","Create professional videos autonomously using claude-code-video-toolkit — AI voiceovers, image generation, music, talking heads, and Remotion rendering.","openclaw-video-toolkit",{"claudeCode":12},"SKILL.md frontmatter at skills/openclaw-video-toolkit/SKILL.md",[386],{"path":285,"priority":286},{"sources":388},[389],"manual",{"closedIssues90d":245,"description":391,"forks":246,"license":252,"openIssues90d":247,"pushedAt":248,"readmeSize":243,"stars":249,"topics":392},"AI-native video production toolkit for Claude Code",[393,394,395,292,396,397,359,398,399,400,401,402,403],"ai-video-generator","claude-code","developer-tools","playwright","programmatic-video","text-to-speech","video-editing","video-production","open-source","qwen-tts","openclaw",{"classifiedAt":405,"discoverAt":406,"extractAt":407,"githubAt":407,"updatedAt":405},1778686219532,1778686211925,1778686217771,[222,217,221,218,223,219,220],{"evaluatedAt":410,"extractAt":411,"updatedAt":255},1778686491299,1778686219732,[],[414,443,471,496,523,555],{"_creationTime":415,"_id":416,"community":417,"display":418,"identity":424,"providers":429,"relations":437,"tags":439,"workflow":440},1778685991755.714,"k17axjt1t8jb33pgs6wy1htxed86mp2k",{"reviewCount":8},{"description":419,"installMethods":420,"name":422,"sourceUrl":423},"Serverless GPU cloud platform for running ML workloads. Use when you need on-demand GPU access without infrastructure management, deploying ML models as APIs, or running batch jobs with automatic scaling.",{"claudeCode":421},"davila7/claude-code-templates","modal-serverless-gpu","https://github.com/davila7/claude-code-templates",{"basePath":425,"githubOwner":426,"githubRepo":427,"locale":288,"slug":428,"type":260},"cli-tool/components/skills/ai-research/infrastructure-modal","davila7","claude-code-templates","infrastructure-modal",{"evaluate":430,"extract":436},{"promptVersionExtension":210,"promptVersionScoring":211,"score":214,"tags":431,"targetMarket":265,"tier":435},[432,220,218,217,433,434],"infrastructure","deployment","mlops","community",{"commitSha":267},{"repoId":438},"kd71fzn4s7r0269fkw47wt670n86ndz0",[217,433,218,432,434,220],{"evaluatedAt":441,"extractAt":442,"updatedAt":441},1778687424295,1778685991755,{"_creationTime":444,"_id":445,"community":446,"display":447,"identity":453,"providers":457,"relations":465,"tags":467,"workflow":468},1778675145461.874,"k17eysxemcay66snayant206gx86mv92",{"reviewCount":8},{"description":448,"installMethods":449,"name":451,"sourceUrl":452},"Part of the AlterLab Academic Skills suite. Run Python code in the cloud with serverless containers, GPUs, and autoscaling. Use when deploying ML models, running batch processing jobs, scheduling compute-intensive tasks, or serving APIs that require GPU acceleration or dynamic scaling.",{"claudeCode":450},"AlterLab-IEU/AlterLab-Academic-Skills","alterlab-modal","https://github.com/AlterLab-IEU/AlterLab-Academic-Skills",{"basePath":454,"githubOwner":455,"githubRepo":456,"locale":288,"slug":451,"type":260},"skills/domain-specific/alterlab-modal","AlterLab-IEU","AlterLab-Academic-Skills",{"evaluate":458,"extract":464},{"promptVersionExtension":210,"promptVersionScoring":211,"score":214,"tags":459,"targetMarket":265,"tier":224},[460,218,220,461,462,463],"python","ml","batch-processing","cloud-compute",{"commitSha":267},{"repoId":466},"kd7fqvj70pvyn4r3q9kctpnd7d86mfqd",[462,463,218,461,460,220],{"evaluatedAt":469,"extractAt":470,"updatedAt":469},1778678411488,1778675145461,{"_creationTime":472,"_id":473,"community":474,"display":475,"identity":479,"providers":484,"relations":489,"tags":492,"workflow":493},1778695116697.1846,"k175v5fe4bt509v7dma1w27wbd86mwg7",{"reviewCount":8},{"description":419,"installMethods":476,"name":422,"sourceUrl":478},{"claudeCode":477},"Orchestra-Research/AI-Research-SKILLs","https://github.com/Orchestra-Research/AI-Research-SKILLs",{"basePath":480,"githubOwner":481,"githubRepo":482,"locale":288,"slug":483,"type":260},"09-infrastructure/modal","Orchestra-Research","AI-Research-SKILLs","modal",{"evaluate":485,"extract":488},{"promptVersionExtension":210,"promptVersionScoring":211,"score":486,"tags":487,"targetMarket":265,"tier":224},95,[432,220,218,217,433,434],{"commitSha":267},{"parentExtensionId":490,"repoId":491},"k17155ws9qc0hw7a568bg79sfd86max8","kd70hj1y80mhra5xm5g188j5n586mg18",[217,433,218,432,434,220],{"evaluatedAt":494,"extractAt":495,"updatedAt":494},1778696387488,1778695116697,{"_creationTime":497,"_id":498,"community":499,"display":500,"identity":506,"providers":510,"relations":517,"tags":519,"workflow":520},1778691799740.482,"k17btnjsa0dksd4m8qbqw19gsx86n687",{"reviewCount":8},{"description":501,"installMethods":502,"name":504,"sourceUrl":505},"Cloud computing platform for running Python on GPUs and serverless infrastructure. Use when deploying AI/ML models, running GPU-accelerated workloads, serving web endpoints, scheduling batch jobs, or scaling Python code to the cloud. Use this skill whenever the user mentions Modal, serverless GPU compute, deploying ML models to the cloud, serving inference endpoints, running batch processing in the cloud, or needs to scale Python workloads beyond their local machine. Also use when the user wants to run code on H100s, A100s, or other cloud GPUs, or needs to create a web API for a model.",{"claudeCode":503},"K-Dense-AI/claude-scientific-skills","Modal","https://github.com/K-Dense-AI/claude-scientific-skills",{"basePath":507,"githubOwner":508,"githubRepo":509,"locale":288,"slug":483,"type":260},"scientific-skills/modal","K-Dense-AI","claude-scientific-skills",{"evaluate":511,"extract":515},{"promptVersionExtension":210,"promptVersionScoring":211,"score":486,"tags":512,"targetMarket":265,"tier":224},[513,460,218,220,222,461,514],"cloud-computing","devops",{"commitSha":267,"license":516},"Apache-2.0",{"repoId":518},"kd79rphh5gexy91xmpxc05h5mh86mm9r",[222,513,514,218,461,460,220],{"evaluatedAt":521,"extractAt":522,"updatedAt":521},1778693236762,1778691799740,{"_creationTime":524,"_id":525,"community":526,"display":527,"identity":533,"providers":538,"relations":548,"tags":551,"workflow":552},1778696691708.3274,"k170az7r02e9e2v47mpy80kx6n86nff3",{"reviewCount":8},{"description":528,"installMethods":529,"name":531,"sourceUrl":532},"Detect current market regime using npx neural-trader — bull/bear/ranging/volatile classification with recommended strategy",{"claudeCode":530},"ruvnet/ruflo","Trader Regime","https://github.com/ruvnet/ruflo",{"basePath":534,"githubOwner":535,"githubRepo":536,"locale":288,"slug":537,"type":260},"plugins/ruflo-neural-trader/skills/trader-regime","ruvnet","ruflo","trader-regime",{"evaluate":539,"extract":547},{"promptVersionExtension":210,"promptVersionScoring":211,"score":540,"tags":541,"targetMarket":265,"tier":224},100,[542,543,544,222,545,546],"finance","trading","market-analysis","typescript","cli",{"commitSha":267,"license":252},{"parentExtensionId":549,"repoId":550},"k17drge8h1fgzchr0p4jaeg33n86mwmy","kd7ed28gj8n0y3msk5dzrp05zs86nqtc",[222,546,542,544,543,545],{"evaluatedAt":553,"extractAt":554,"updatedAt":553},1778701108877,1778696691708,{"_creationTime":556,"_id":557,"community":558,"display":559,"identity":565,"providers":569,"relations":574,"tags":578,"workflow":579},1778693819389.531,"k174n8dznk7k8dr9drb7fwx01586nm5t",{"reviewCount":8},{"description":560,"installMethods":561,"name":563,"sourceUrl":564},"AI交易记忆的领域知识 — 结果加权记忆 (OWM) 架构、5种记忆类型、回忆评分和行为分析。用于记录交易、回忆相似的上下文、分析性能或检查行为漂移。在 \"record trade\"、\"remember trade\"、\"recall\"、\"similar trades\"、\"performance\"、\"behavioral\"、\"disposition\"、\"affective state\"、\"confidence\" 时触发。",{"claudeCode":562},"mnemox-ai/tradememory-protocol","trading-memory","https://github.com/mnemox-ai/tradememory-protocol",{"basePath":566,"githubOwner":567,"githubRepo":568,"locale":18,"slug":563,"type":260},"tradememory-plugin/skills/trading-memory","mnemox-ai","tradememory-protocol",{"evaluate":570,"extract":573},{"promptVersionExtension":210,"promptVersionScoring":211,"score":540,"tags":571,"targetMarket":265,"tier":224},[543,222,572,542,460],"memory",{"commitSha":267},{"parentExtensionId":575,"repoId":576,"translatedFrom":577},"k170vxkqee48k2xq1v55a025nh86nzn7","kd73z11kfekksxyrs8ds0snacs86ncdy","k173a67a16bpq0e29wjd85v71986nx03",[222,542,572,460,543],{"evaluatedAt":580,"extractAt":581,"updatedAt":582},1778693719816,1778693539593,1778693819389]