[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"extension-skill-digitalsamba-runpod-en":3,"guides-for-digitalsamba-runpod":409,"similar-k17ezctet9954yj232ppmq7b5d86mrx7-en":410},{"_creationTime":4,"_id":5,"children":6,"community":7,"display":9,"evaluation":15,"identity":257,"isFallback":252,"parentExtension":262,"providers":263,"relations":268,"repo":270,"tags":405,"workflow":406},1778686219732.8728,"k17ezctet9954yj232ppmq7b5d86mrx7",[],{"reviewCount":8},0,{"description":10,"installMethods":11,"name":13,"sourceUrl":14},"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},"digitalsamba/claude-code-video-toolkit","RunPod Cloud GPU","https://github.com/digitalsamba/claude-code-video-toolkit",{"_creationTime":16,"_id":17,"extensionId":5,"locale":18,"result":19,"trustSignals":238,"workflow":255},1778686491298.8987,"kn70wvnp34w1enp5e5c1hhecws86ncqe","en",{"checks":20,"evaluatedAt":192,"extensionSummary":193,"features":194,"nonGoals":200,"practices":205,"prerequisites":206,"promptVersionExtension":210,"promptVersionScoring":211,"purpose":212,"rationale":213,"score":214,"summary":215,"tags":216,"targetMarket":224,"tier":225,"useCases":226,"workflow":232},[21,26,29,32,36,39,44,48,51,54,58,62,65,69,72,75,78,81,84,87,91,95,99,103,107,110,113,116,120,123,126,129,132,135,138,142,146,150,153,157,160,163,166,169,173,176,179,182,185,189],{"category":22,"check":23,"severity":24,"summary":25},"Practical Utility","Problem relevance","pass","The description clearly states the problem of managing cloud GPU processing for AI models via RunPod serverless and lists specific use cases like setup, deployment, resource management, and troubleshooting.",{"category":22,"check":27,"severity":24,"summary":28},"Unique selling proposition","The skill provides a structured workflow for setting up and managing cloud GPU resources, including API references and troubleshooting, which goes beyond a simple API wrapper.",{"category":22,"check":30,"severity":24,"summary":31},"Production readiness","The skill covers the complete lifecycle for managing RunPod endpoints, from setup and deployment to management and troubleshooting, making it ready for production use.",{"category":33,"check":34,"severity":24,"summary":35},"Scope","Single responsibility principle","The skill focuses solely on managing RunPod cloud GPU resources and related Docker images, adhering to a single domain.",{"category":33,"check":37,"severity":24,"summary":38},"Description quality","The displayed description accurately reflects the skill's functionality as detailed in the SKILL.md, covering RunPod setup, management, and specific toolkit images.",{"category":40,"check":41,"severity":42,"summary":43},"Invocation","Scoped tools","not_applicable","This skill is not a CLI or MCP that exposes tools directly; it acts as a unified interface for managing RunPod resources.",{"category":45,"check":46,"severity":24,"summary":47},"Documentation","Configuration & parameter reference","The SKILL.md provides detailed API references for GraphQL and REST, including authentication, field names, and common mistakes, and explains environment variable setup for RunPod and Cloudflare R2.",{"category":33,"check":49,"severity":42,"summary":50},"Tool naming","The skill does not expose individual tools with names; rather, it orchestrates API calls and setup procedures.",{"category":33,"check":52,"severity":42,"summary":53},"Minimal I/O surface","As this skill primarily interacts with external APIs and manages configurations, the concept of minimal I/O surface for individual tools does not directly apply.",{"category":55,"check":56,"severity":24,"summary":57},"License","License usability","The extension is licensed under the MIT License, which is a permissive open-source license.",{"category":59,"check":60,"severity":24,"summary":61},"Maintenance","Commit recency","The repository has recent commits within the last 3 months, indicating active maintenance.",{"category":59,"check":63,"severity":24,"summary":64},"Dependency Management","The project uses a requirements.txt for Python dependencies and a package.json for frontend dependencies, and the README suggests using pip for installation, indicating dependency management practices.",{"category":66,"check":67,"severity":24,"summary":68},"Security","Secret Management","Secrets like RUNPOD_API_KEY are handled via .env files and not hardcoded in scripts, adhering to good secret management practices.",{"category":66,"check":70,"severity":24,"summary":71},"Injection","The skill focuses on managing external API interactions and does not load or execute untrusted third-party code.",{"category":66,"check":73,"severity":24,"summary":74},"Transitive Supply-Chain Grenades","The skill does not fetch remote code or data at runtime; all necessary configurations and API interactions are managed within the provided scripts and documentation.",{"category":66,"check":76,"severity":24,"summary":77},"Sandbox Isolation","The skill interacts with external APIs and manages configurations, and there are no indications of it attempting to modify files or paths outside its intended scope.",{"category":66,"check":79,"severity":24,"summary":80},"Sandbox escape primitives","No detached-process spawns or deny-retry loops were found in the provided scripts.",{"category":66,"check":82,"severity":24,"summary":83},"Data Exfiltration","The skill only requires an API key for RunPod and handles it via environment variables, with no indications of exfiltrating confidential data.",{"category":66,"check":85,"severity":24,"summary":86},"Hidden Text Tricks","The bundled content is free of hidden-steering tricks and uses clean, printable ASCII.",{"category":88,"check":89,"severity":24,"summary":90},"Hooks","Opaque code execution","The scripts in the bundle are plain and readable, with no obfuscation like base64 payloads or runtime fetched code.",{"category":92,"check":93,"severity":24,"summary":94},"Portability","Structural Assumption","The skill relies on environment variables for configuration and API keys, making it portable without assumptions about project structure.",{"category":96,"check":97,"severity":24,"summary":98},"Trust","Issues Attention","With 1 open issue and 4 closed issues in the last 90 days, the closure rate is sufficient, indicating good maintainer engagement.",{"category":100,"check":101,"severity":24,"summary":102},"Versioning","Release Management","The repository has GitHub release tags and a CHANGELOG.md, providing clear versioning signals.",{"category":104,"check":105,"severity":42,"summary":106},"Code Execution","Validation","The skill primarily manages configurations and interacts with external APIs. No complex input validation schemas are directly exposed or required by the skill itself.",{"category":66,"check":108,"severity":24,"summary":109},"Unguarded Destructive Operations","Operations like endpoint setup and image deployment are managed through explicit commands and API calls, not destructive CLI operations.",{"category":104,"check":111,"severity":24,"summary":112},"Error Handling","The documentation provides troubleshooting steps and common mistakes, implying reasonable error handling for API interactions and setup processes.",{"category":104,"check":114,"severity":42,"summary":115},"Logging","As this skill interacts with external APIs and manages configurations rather than performing local destructive actions, a dedicated local audit log is not applicable.",{"category":117,"check":118,"severity":42,"summary":119},"Compliance","GDPR","The skill does not operate on personal data; it manages cloud GPU resources and API keys.",{"category":117,"check":121,"severity":24,"summary":122},"Target market","The extension is globally applicable and does not have any regional or jurisdictional limitations.",{"category":92,"check":124,"severity":24,"summary":125},"Runtime stability","The skill relies on standard Python and environment variables, making it portable across different POSIX shells and operating systems.",{"category":45,"check":127,"severity":24,"summary":128},"README","The README provides a comprehensive overview of the toolkit, its features, setup instructions, and examples.",{"category":33,"check":130,"severity":42,"summary":131},"Tool surface size","This skill is not a CLI or MCP that exposes individual tools; it's a unified interface for managing RunPod.",{"category":40,"check":133,"severity":42,"summary":134},"Overlapping near-synonym tools","The skill does not expose multiple tools that are near-synonyms; it orchestrates a single workflow.",{"category":45,"check":136,"severity":24,"summary":137},"Phantom features","All features mentioned in the README, such as RunPod setup and management, have corresponding implementations or detailed documentation in the SKILL.md and provided scripts.",{"category":139,"check":140,"severity":24,"summary":141},"Install","Installation instruction","The README provides clear, copy-pasteable installation instructions for the Python requirements and guidance on setting up environment variables for RunPod API keys.",{"category":143,"check":144,"severity":24,"summary":145},"Errors","Actionable error messages","The SKILL.md includes a troubleshooting section that outlines common errors, their symptoms, and remediation steps, providing actionable guidance.",{"category":147,"check":148,"severity":24,"summary":149},"Execution","Pinned dependencies","The `tools/requirements.txt` file pins Python dependencies, and the README suggests installing them via pip, ensuring reproducible environments.",{"category":33,"check":151,"severity":42,"summary":152},"Dry-run preview","The skill's primary functions involve setup and API interaction, not direct state-changing operations that would benefit from a dry-run preview.",{"category":154,"check":155,"severity":24,"summary":156},"Protocol","Idempotent retry & timeouts","The documentation implicitly suggests retries for API calls and mentions handling job status polling, indicating consideration for operation stability.",{"category":117,"check":158,"severity":24,"summary":159},"Telemetry opt-in","There is no indication of telemetry being collected by this skill; all operations are local configuration and API interaction.",{"category":40,"check":161,"severity":24,"summary":162},"Precise Purpose","The skill's purpose is precisely defined as managing Cloud GPU processing via RunPod serverless, with clear triggers for setup, deployment, resource management, and troubleshooting.",{"category":40,"check":164,"severity":24,"summary":165},"Concise Frontmatter","The frontmatter in SKILL.md is concise and effectively summarizes the skill's core capability and usage scenarios within the character limit.",{"category":45,"check":167,"severity":24,"summary":168},"Concise Body","The SKILL.md is well-structured and avoids unnecessary verbosity, delegating detailed API references to specific sections.",{"category":170,"check":171,"severity":24,"summary":172},"Context","Progressive Disclosure","Detailed API references are provided in specific sections within the SKILL.md, adhering to progressive disclosure principles.",{"category":170,"check":174,"severity":42,"summary":175},"Forked exploration","This skill is focused on management and setup, not deep exploration or code review, so 'context: fork' is not applicable.",{"category":22,"check":177,"severity":24,"summary":178},"Usage examples","The SKILL.md includes clear command-line examples for setup and deployment, with expected outcomes described.",{"category":22,"check":180,"severity":24,"summary":181},"Edge cases","The troubleshooting section in SKILL.md addresses common issues like slow cold starts, OOM errors, and worker availability, with documented recovery steps.",{"category":104,"check":183,"severity":42,"summary":184},"Tool Fallback","This skill does not rely on external tools that require a fallback; it interacts directly with the RunPod API.",{"category":186,"check":187,"severity":24,"summary":188},"Safety","Halt on unexpected state","The setup process implies a structured workflow, and the troubleshooting section indicates that failures will halt the process, prompting user intervention.",{"category":92,"check":190,"severity":24,"summary":191},"Cross-skill coupling","This skill operates independently and does not implicitly rely on other skills being loaded in the same session.",1778686491172,"This skill provides a comprehensive interface for interacting with RunPod serverless, enabling users to set up, deploy Docker images, manage GPU resources, and understand costs. It covers the setup and management of five specific toolkit images, including detailed API references and troubleshooting guidance.",[195,196,197,198,199],"Setup and deployment of RunPod endpoints","Management of GPU resources and Docker images","Troubleshooting endpoint issues","Detailed RunPod API reference (GraphQL and REST)","Cost understanding and optimization guidance",[201,202,203,204],"Directly running AI models locally","Managing local machine hardware","Providing a general-purpose cloud management tool","Replacing the RunPod web console for all tasks",[],[207,208,209],"RunPod account and API key","Cloudflare R2 credentials (optional, for file transfer fallback)","Python 3.9+ recommended","3.0.0","4.4.0","To enable users to leverage cloud GPU processing through RunPod serverless for deploying and managing AI models and Docker images efficiently.","The skill demonstrates excellent documentation, security, and production readiness, with all checks passing or being not applicable. The extensive documentation and clear setup instructions contribute to a high score.",98,"Excellent skill for managing cloud GPU resources via RunPod serverless.",[217,218,219,220,221,222,223],"cloud","gpu","runpod","serverless","docker","ai","machine-learning","global","verified",[227,228,229,230,231],"When setting up RunPod endpoints for AI model deployment","Deploying custom Docker images to cloud GPUs","Managing GPU resources and scaling configurations","Troubleshooting issues with RunPod endpoints","Understanding and optimizing cloud GPU costs",[233,234,235,236,237],"Add RunPod API key to .env","Run `--setup` for specific tools (image_edit, upscale, etc.)","Configure endpoint workers (min/max, idleTimeout)","Manage endpoints via RunPod dashboard or API reference","Troubleshoot common issues (cold start, OOM, worker availability)",{"codeQuality":239,"collectedAt":241,"documentation":242,"maintenance":245,"security":251,"testCoverage":254},{"hasLockfile":240},true,1778686468546,{"descriptionLength":243,"readmeSize":244},274,18886,{"closedIssues90d":246,"forks":247,"hasChangelog":240,"openIssues90d":248,"pushedAt":249,"stars":250},4,187,1,1778501732000,1137,{"hasNpmPackage":252,"license":253,"smitheryVerified":252},false,"MIT",{"hasCi":240,"hasTests":252},{"updatedAt":256},1778686491299,{"basePath":258,"githubOwner":259,"githubRepo":260,"locale":18,"slug":219,"type":261},".claude/skills/runpod","digitalsamba","claude-code-video-toolkit","skill",null,{"evaluate":264,"extract":266},{"promptVersionExtension":210,"promptVersionScoring":211,"score":214,"tags":265,"targetMarket":224,"tier":225},[217,218,219,220,221,222,223],{"commitSha":267,"license":253},"HEAD",{"repoId":269},"kd70r97eght58pp9f1x8scdagd86n32q",{"_creationTime":271,"_id":269,"identity":272,"providers":273,"workflow":401},1778686211924.9185,{"githubOwner":259,"githubRepo":260,"sourceUrl":14},{"classify":274,"discover":384,"github":387},{"commitSha":267,"extensions":275},[276,287,298,307,315,323,331,340,354,363,371,376],{"basePath":277,"description":278,"displayName":279,"installMethods":280,"rationale":281,"selectedPaths":282,"source":286,"sourceLanguage":18,"type":261},".claude/skills/acestep","AI 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",[283],{"path":284,"priority":285},"SKILL.md","mandatory","rule",{"basePath":288,"description":289,"displayName":290,"installMethods":291,"rationale":292,"selectedPaths":293,"source":286,"sourceLanguage":18,"type":261},".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",[294,295],{"path":284,"priority":285},{"path":296,"priority":297},"reference.md","medium",{"basePath":299,"description":300,"displayName":301,"installMethods":302,"rationale":303,"selectedPaths":304,"source":286,"sourceLanguage":18,"type":261},".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",[305,306],{"path":284,"priority":285},{"path":296,"priority":297},{"basePath":308,"description":309,"displayName":310,"installMethods":311,"rationale":312,"selectedPaths":313,"source":286,"sourceLanguage":18,"type":261},".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",[314],{"path":284,"priority":285},{"basePath":316,"description":317,"displayName":318,"installMethods":319,"rationale":320,"selectedPaths":321,"source":286,"sourceLanguage":18,"type":261},".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",[322],{"path":284,"priority":285},{"basePath":324,"description":325,"displayName":326,"installMethods":327,"rationale":328,"selectedPaths":329,"source":286,"sourceLanguage":18,"type":261},".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",[330],{"path":284,"priority":285},{"basePath":332,"description":333,"displayName":334,"installMethods":335,"rationale":336,"selectedPaths":337,"source":286,"sourceLanguage":18,"type":261},".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",[338,339],{"path":284,"priority":285},{"path":296,"priority":297},{"basePath":341,"description":342,"displayName":343,"installMethods":344,"rationale":345,"selectedPaths":346,"source":286,"sourceLanguage":18,"type":261},".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",[347,348,350,352],{"path":284,"priority":285},{"path":349,"priority":297},"examples.md",{"path":351,"priority":297},"parameters.md",{"path":353,"priority":297},"prompting.md",{"basePath":355,"description":356,"displayName":357,"installMethods":358,"rationale":359,"selectedPaths":360,"source":286,"sourceLanguage":18,"type":261},".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",[361,362],{"path":284,"priority":285},{"path":296,"priority":297},{"basePath":364,"description":365,"displayName":366,"installMethods":367,"rationale":368,"selectedPaths":369,"source":286,"sourceLanguage":18,"type":261},".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",[370],{"path":284,"priority":285},{"basePath":258,"description":10,"displayName":219,"installMethods":372,"rationale":373,"selectedPaths":374,"source":286,"sourceLanguage":18,"type":261},{"claudeCode":12},"SKILL.md frontmatter at .claude/skills/runpod/SKILL.md",[375],{"path":284,"priority":285},{"basePath":377,"description":378,"displayName":379,"installMethods":380,"rationale":381,"selectedPaths":382,"source":286,"sourceLanguage":18,"type":261},"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",[383],{"path":284,"priority":285},{"sources":385},[386],"manual",{"closedIssues90d":246,"description":388,"forks":247,"license":253,"openIssues90d":248,"pushedAt":249,"readmeSize":244,"stars":250,"topics":389},"AI-native video production toolkit for Claude Code",[390,391,392,290,393,394,357,395,396,397,398,399,400],"ai-video-generator","claude-code","developer-tools","playwright","programmatic-video","text-to-speech","video-editing","video-production","open-source","qwen-tts","openclaw",{"classifiedAt":402,"discoverAt":403,"extractAt":404,"githubAt":404,"updatedAt":402},1778686219532,1778686211925,1778686217771,[222,217,221,218,223,219,220],{"evaluatedAt":256,"extractAt":407,"updatedAt":408},1778686219732,1778686650196,[],[411,440,468,493,520,552],{"_creationTime":412,"_id":413,"community":414,"display":415,"identity":421,"providers":426,"relations":434,"tags":436,"workflow":437},1778685991755.714,"k17axjt1t8jb33pgs6wy1htxed86mp2k",{"reviewCount":8},{"description":416,"installMethods":417,"name":419,"sourceUrl":420},"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":418},"davila7/claude-code-templates","modal-serverless-gpu","https://github.com/davila7/claude-code-templates",{"basePath":422,"githubOwner":423,"githubRepo":424,"locale":18,"slug":425,"type":261},"cli-tool/components/skills/ai-research/infrastructure-modal","davila7","claude-code-templates","infrastructure-modal",{"evaluate":427,"extract":433},{"promptVersionExtension":210,"promptVersionScoring":211,"score":214,"tags":428,"targetMarket":224,"tier":432},[429,220,218,217,430,431],"infrastructure","deployment","mlops","community",{"commitSha":267},{"repoId":435},"kd71fzn4s7r0269fkw47wt670n86ndz0",[217,430,218,429,431,220],{"evaluatedAt":438,"extractAt":439,"updatedAt":438},1778687424295,1778685991755,{"_creationTime":441,"_id":442,"community":443,"display":444,"identity":450,"providers":454,"relations":462,"tags":464,"workflow":465},1778675145461.874,"k17eysxemcay66snayant206gx86mv92",{"reviewCount":8},{"description":445,"installMethods":446,"name":448,"sourceUrl":449},"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":447},"AlterLab-IEU/AlterLab-Academic-Skills","alterlab-modal","https://github.com/AlterLab-IEU/AlterLab-Academic-Skills",{"basePath":451,"githubOwner":452,"githubRepo":453,"locale":18,"slug":448,"type":261},"skills/domain-specific/alterlab-modal","AlterLab-IEU","AlterLab-Academic-Skills",{"evaluate":455,"extract":461},{"promptVersionExtension":210,"promptVersionScoring":211,"score":214,"tags":456,"targetMarket":224,"tier":225},[457,218,220,458,459,460],"python","ml","batch-processing","cloud-compute",{"commitSha":267},{"repoId":463},"kd7fqvj70pvyn4r3q9kctpnd7d86mfqd",[459,460,218,458,457,220],{"evaluatedAt":466,"extractAt":467,"updatedAt":466},1778678411488,1778675145461,{"_creationTime":469,"_id":470,"community":471,"display":472,"identity":476,"providers":481,"relations":486,"tags":489,"workflow":490},1778695116697.1846,"k175v5fe4bt509v7dma1w27wbd86mwg7",{"reviewCount":8},{"description":416,"installMethods":473,"name":419,"sourceUrl":475},{"claudeCode":474},"Orchestra-Research/AI-Research-SKILLs","https://github.com/Orchestra-Research/AI-Research-SKILLs",{"basePath":477,"githubOwner":478,"githubRepo":479,"locale":18,"slug":480,"type":261},"09-infrastructure/modal","Orchestra-Research","AI-Research-SKILLs","modal",{"evaluate":482,"extract":485},{"promptVersionExtension":210,"promptVersionScoring":211,"score":483,"tags":484,"targetMarket":224,"tier":225},95,[429,220,218,217,430,431],{"commitSha":267},{"parentExtensionId":487,"repoId":488},"k17155ws9qc0hw7a568bg79sfd86max8","kd70hj1y80mhra5xm5g188j5n586mg18",[217,430,218,429,431,220],{"evaluatedAt":491,"extractAt":492,"updatedAt":491},1778696387488,1778695116697,{"_creationTime":494,"_id":495,"community":496,"display":497,"identity":503,"providers":507,"relations":514,"tags":516,"workflow":517},1778691799740.482,"k17btnjsa0dksd4m8qbqw19gsx86n687",{"reviewCount":8},{"description":498,"installMethods":499,"name":501,"sourceUrl":502},"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":500},"K-Dense-AI/claude-scientific-skills","Modal","https://github.com/K-Dense-AI/claude-scientific-skills",{"basePath":504,"githubOwner":505,"githubRepo":506,"locale":18,"slug":480,"type":261},"scientific-skills/modal","K-Dense-AI","claude-scientific-skills",{"evaluate":508,"extract":512},{"promptVersionExtension":210,"promptVersionScoring":211,"score":483,"tags":509,"targetMarket":224,"tier":225},[510,457,218,220,222,458,511],"cloud-computing","devops",{"commitSha":267,"license":513},"Apache-2.0",{"repoId":515},"kd79rphh5gexy91xmpxc05h5mh86mm9r",[222,510,511,218,458,457,220],{"evaluatedAt":518,"extractAt":519,"updatedAt":518},1778693236762,1778691799740,{"_creationTime":521,"_id":522,"community":523,"display":524,"identity":530,"providers":535,"relations":545,"tags":548,"workflow":549},1778696691708.3274,"k170az7r02e9e2v47mpy80kx6n86nff3",{"reviewCount":8},{"description":525,"installMethods":526,"name":528,"sourceUrl":529},"Detect current market regime using npx neural-trader — bull/bear/ranging/volatile classification with recommended strategy",{"claudeCode":527},"ruvnet/ruflo","Trader Regime","https://github.com/ruvnet/ruflo",{"basePath":531,"githubOwner":532,"githubRepo":533,"locale":18,"slug":534,"type":261},"plugins/ruflo-neural-trader/skills/trader-regime","ruvnet","ruflo","trader-regime",{"evaluate":536,"extract":544},{"promptVersionExtension":210,"promptVersionScoring":211,"score":537,"tags":538,"targetMarket":224,"tier":225},100,[539,540,541,222,542,543],"finance","trading","market-analysis","typescript","cli",{"commitSha":267,"license":253},{"parentExtensionId":546,"repoId":547},"k17drge8h1fgzchr0p4jaeg33n86mwmy","kd7ed28gj8n0y3msk5dzrp05zs86nqtc",[222,543,539,541,540,542],{"evaluatedAt":550,"extractAt":551,"updatedAt":550},1778701108877,1778696691708,{"_creationTime":553,"_id":554,"community":555,"display":556,"identity":562,"providers":566,"relations":571,"tags":574,"workflow":575},1778693539593.1863,"k173a67a16bpq0e29wjd85v71986nx03",{"reviewCount":8},{"description":557,"installMethods":558,"name":560,"sourceUrl":561},"Domain knowledge for AI trading memory — Outcome-Weighted Memory (OWM) architecture, 5 memory types, recall scoring, and behavioral analysis. Use when recording trades, recalling similar contexts, analyzing performance, or checking behavioral drift. Triggers on \"record trade\", \"remember trade\", \"recall\", \"similar trades\", \"performance\", \"behavioral\", \"disposition\", \"affective state\", \"confidence\".",{"claudeCode":559},"mnemox-ai/tradememory-protocol","trading-memory","https://github.com/mnemox-ai/tradememory-protocol",{"basePath":563,"githubOwner":564,"githubRepo":565,"locale":18,"slug":560,"type":261},"tradememory-plugin/skills/trading-memory","mnemox-ai","tradememory-protocol",{"evaluate":567,"extract":570},{"promptVersionExtension":210,"promptVersionScoring":211,"score":537,"tags":568,"targetMarket":224,"tier":225},[540,222,569,539,457],"memory",{"commitSha":267},{"parentExtensionId":572,"repoId":573},"k170vxkqee48k2xq1v55a025nh86nzn7","kd73z11kfekksxyrs8ds0snacs86ncdy",[222,539,569,457,540],{"evaluatedAt":576,"extractAt":577,"updatedAt":578},1778693719816,1778693539593,1778693833320]