[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"extension-skill-digitalsamba-moviepy-tr":3,"guides-for-digitalsamba-moviepy":237,"similar-k170hmpw30n48369dk2qgfte95866a9x":238},{"_creationTime":4,"_id":5,"children":6,"community":7,"display":9,"evaluation":21,"identity":188,"isFallback":192,"parentExtension":193,"providers":194,"relations":199,"repo":201,"workflow":234},1778054035325.8765,"k170hmpw30n48369dk2qgfte95866a9x",[],{"reviewCount":8},0,{"description":10,"installMethods":11,"name":12,"sourceUrl":13,"tags":14},"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 for Video Production","https://github.com/digitalsamba/claude-code-video-toolkit/tree/HEAD/.claude/skills/moviepy",[15,16,17,18,19,20],"video","python","moviepy","composition","text-overlay","ai-video",{"_creationTime":22,"_id":23,"extensionId":5,"locale":24,"result":25,"trustSignals":177,"workflow":186},1778054079849.1348,"kn7d4d7t7w55pxz63xqffn3k318670jz","en",{"checks":26,"evaluatedAt":167,"extensionSummary":168,"promptVersionExtension":169,"promptVersionScoring":170,"rationale":171,"score":172,"summary":173,"tags":174,"targetMarket":175,"tier":176},[27,32,35,38,42,45,49,53,56,59,63,68,71,75,78,81,84,87,90,93,96,100,104,108,113,116,119,122,126,129,132,135,138,141,145,148,151,154,157,160,164],{"category":28,"check":29,"severity":30,"summary":31},"Practical Utility","Problem relevance","pass","The description clearly names a concrete user problem: overlaying deterministic text on AI-generated video and building single-file Python video projects, specifically addressing the unreliability of in-frame text from AI models.",{"category":28,"check":33,"severity":30,"summary":34},"Unique selling proposition","The extension offers significant value over a simple prompt by providing a dedicated moviepy-based workflow for deterministic text overlays and programmatic video composition, which is a distinct capability beyond basic AI video generation.",{"category":28,"check":36,"severity":30,"summary":37},"Production readiness","The extension provides runnable examples and detailed instructions on dependencies and usage, covering the complete lifecycle for its stated use case of text overlay and video composition.",{"category":39,"check":40,"severity":30,"summary":41},"Scope","Single responsibility principle","The extension focuses on Python video composition using moviepy, specifically for overlaying deterministic text and compositing clips, which is a coherent and single domain.",{"category":39,"check":43,"severity":30,"summary":44},"Description quality","The description is accurate, concise, readable, and accurately reflects the extension's behavior, detailing its use cases and triggers.",{"category":46,"check":47,"severity":30,"summary":48},"Invocation","Scoped tools","The extension utilizes moviepy's specific functions for video manipulation (e.g., `VideoFileClip`, `ImageClip`, `CompositeVideoClip`) which are narrow and domain-specific, rather than a single generalist execution tool.",{"category":50,"check":51,"severity":30,"summary":52},"Documentation","Configuration & parameter reference","The SKILL.md provides detailed code examples and explains the purpose of key functions and the overall workflow, including dependency management.",{"category":39,"check":54,"severity":30,"summary":55},"Tool naming","The extension does not expose user-facing tools directly but rather provides Python functions and scripts demonstrating moviepy usage, which are descriptively named within the examples and documentation.",{"category":39,"check":57,"severity":30,"summary":58},"Minimal I/O surface","The Python code examples demonstrate specific and minimal inputs required for moviepy operations, such as video file paths and text parameters, and produce well-defined video file outputs.",{"category":60,"check":61,"severity":30,"summary":62},"License","License usability","The repository contains a standard MIT license file, clearly indicating permissive open-source usage.",{"category":64,"check":65,"severity":66,"summary":67},"Maintenance","Commit recency","not_applicable","No commit data is available for evaluation.",{"category":64,"check":69,"severity":30,"summary":70},"Dependency Management","The extension explicitly lists dependencies in `tools/requirements.txt` and provides clear instructions for installation, ensuring proper management.",{"category":72,"check":73,"severity":66,"summary":74},"Security","Secret Management","The extension does not appear to handle or require any secrets for its core functionality.",{"category":72,"check":76,"severity":30,"summary":77},"Injection","The extension's code examples use moviepy functions directly with documented inputs, and there's no indication of loading untrusted external data as executable instructions.",{"category":72,"check":79,"severity":30,"summary":80},"Transitive Supply-Chain Grenades","All dependencies are managed via `requirements.txt`, and the code executes locally without runtime fetching of code or data that could be manipulated.",{"category":72,"check":82,"severity":30,"summary":83},"Sandbox Isolation","The Python scripts operate on specified input files and produce output files within the project directory, adhering to sandbox isolation principles.",{"category":72,"check":85,"severity":30,"summary":86},"Sandbox escape primitives","The provided Python code does not contain detached process spawns or retry loops around denied tool calls.",{"category":72,"check":88,"severity":30,"summary":89},"Data Exfiltration","The extension's functionality is limited to local video file manipulation and does not involve outbound calls to submit confidential data.",{"category":72,"check":91,"severity":30,"summary":92},"Hidden Text Tricks","The bundled markdown and Python files do not contain any hidden-steering tricks, invisible Unicode characters, or other obfuscation methods.",{"category":72,"check":94,"severity":30,"summary":95},"Opaque code execution","The Python code is directly readable and not obfuscated through base64 payloads, eval, or runtime fetches.",{"category":97,"check":98,"severity":30,"summary":99},"Portability","Structural Assumption","The examples use relative paths and clearly define preconditions for dependencies, with graceful fallback mechanisms explained.",{"category":101,"check":102,"severity":66,"summary":103},"Trust","Issues Attention","No issue data is available for evaluation.",{"category":105,"check":106,"severity":66,"summary":107},"Versioning","Release Management","No manifest version or release tags are present.",{"category":109,"check":110,"severity":111,"summary":112},"Code Execution","Validation","info","While the Python code handles inputs like file paths and parameters, there is no explicit mention or use of a schema validation library for these inputs.",{"category":72,"check":114,"severity":30,"summary":115},"Unguarded Destructive Operations","The extension performs file operations like writing video files, but these are not inherently destructive in a way that requires additional guards, and they are confined to output directories.",{"category":109,"check":117,"severity":30,"summary":118},"Error Handling","The provided Python code snippets include basic error handling for missing dependencies and file operations, with informative messages and clean exits.",{"category":109,"check":120,"severity":66,"summary":121},"Logging","The extension does not perform destructive actions or outbound calls that would necessitate a local audit log.",{"category":123,"check":124,"severity":66,"summary":125},"Compliance","GDPR","The extension operates on video files and does not process personal data.",{"category":123,"check":127,"severity":30,"summary":128},"Target market","The extension is a general-purpose video composition tool with no regional or jurisdictional logic, therefore the target market is global.",{"category":97,"check":130,"severity":30,"summary":131},"Runtime stability","The extension's Python scripts are generally portable, relying on standard libraries and clearly listing Python dependencies.",{"category":46,"check":133,"severity":30,"summary":134},"Precise Purpose","The description clearly states the extension's purpose (Python video composition with moviepy for deterministic text overlays) and its use cases (e.g., adding labels to AI video, building short ad spots).",{"category":46,"check":136,"severity":30,"summary":137},"Concise Frontmatter","The frontmatter (name and description) is concise and effectively summarizes the core capability and use cases.",{"category":50,"check":139,"severity":30,"summary":140},"Concise Body","The SKILL.md body is well-structured, uses progressive disclosure via examples, and stays within reasonable length limits.",{"category":142,"check":143,"severity":30,"summary":144},"Context","Progressive Disclosure","The SKILL.md effectively uses inline code examples and links to external runnable examples (`examples/`) for progressive disclosure.",{"category":142,"check":146,"severity":66,"summary":147},"Forked exploration","This skill is not an exploration-focused skill that would require forked context.",{"category":28,"check":149,"severity":30,"summary":150},"Usage examples","The SKILL.md provides multiple runnable Python examples (`build.py`) for key use cases like ad spots and data visualizations, demonstrating input, invocation, and expected output.",{"category":28,"check":152,"severity":111,"summary":153},"Edge cases","While the documentation mentions potential issues like `TextClip` bugs and dependency errors, it doesn't explicitly list and document failure modes with recovery steps for every scenario.",{"category":109,"check":155,"severity":66,"summary":156},"Tool Fallback","This extension does not appear to rely on external, optional tools like an MCP server.",{"category":97,"check":158,"severity":30,"summary":159},"Stack assumptions","The extension declares its Python dependencies and provides clear installation instructions, making stack assumptions explicit.",{"category":161,"check":162,"severity":30,"summary":163},"Safety","Halt on unexpected state","The Python scripts handle dependency errors and file operations gracefully, exiting with informative messages rather than proceeding in an unexpected state.",{"category":97,"check":165,"severity":30,"summary":166},"Cross-skill coupling","The moviepy skill is self-contained and does not implicitly rely on other skills; references to other skills are contextual and optional.",1778054062758,"This skill utilizes the moviepy library to overlay deterministic text onto AI-generated video outputs (like LTX-2 or SadTalker) and to build programmatic video projects. It provides clear Python code examples for various use cases, including text rendering via PIL, audio-anchored timelines, and compositing, with detailed instructions on dependencies and potential gotchas.","2.0.0","3.4.0","The extension is well-documented, provides clear and runnable examples, and adheres to best practices for code execution and security. Its purpose is precisely defined, and it focuses on a specific domain without unnecessary scope creep. A minor info finding for edge case documentation prevents a perfect score.",95,"A well-crafted Python skill for deterministic video composition using moviepy, excellent for adding text overlays to AI-generated footage.",[15,16,17,18,19,20],"global","verified",{"codeQuality":178,"collectedAt":179,"documentation":180,"maintenance":182,"security":183,"testCoverage":185},{},1778054051903,{"descriptionLength":181,"readmeSize":8},516,{},{"hasNpmPackage":184,"smitheryVerified":184},false,{"hasCi":184,"hasTests":184},{"updatedAt":187},1778054079849,{"githubOwner":189,"githubRepo":190,"locale":24,"slug":17,"type":191},"digitalsamba","claude-code-video-toolkit","skill",true,null,{"extract":195,"llm":198},{"commitSha":196,"license":197},"dc1bbd251ef137bde9cf460bacb88f13adb3a808","MIT-0",{"promptVersionExtension":169,"promptVersionScoring":170,"score":172,"targetMarket":175,"tier":176},{"repoId":200},"kd77w77a4w1f7nnb9v4fmh2eb1865dn1",{"_creationTime":202,"_id":200,"identity":203,"providers":205,"workflow":231},1777995558409.8706,{"githubOwner":189,"githubRepo":190,"sourceUrl":204},"https://github.com/digitalsamba/claude-code-video-toolkit",{"discover":206,"github":209},{"sources":207},[208],"skills-sh",{"closedIssues90d":210,"forks":211,"license":212,"openIssues90d":213,"pushedAt":214,"readmeSize":215,"stars":216,"topics":217},3,174,"MIT",1,1777892879000,16637,1060,[218,219,220,221,222,223,224,225,226,227,228,229,230],"ai-video-generator","claude-code","developer-tools","elevenlabs","playwright","programmatic-video","remotion","text-to-speech","video-editing","video-production","open-source","qwen-tts","openclaw",{"discoverAt":232,"extractAt":233,"githubAt":233,"updatedAt":233},1777995558409,1778054036987,{"anyEnrichmentAt":235,"extractAt":236,"githubAt":235,"llmAt":187,"updatedAt":187},1778054036248,1778054035325,[],[239,258,293,321,343,369],{"_creationTime":240,"_id":241,"community":242,"display":243,"identity":251,"providers":253,"relations":256,"workflow":257},1778054035325.8784,"k17229shv3rzk51qc5jmm60yxh867meh",{"reviewCount":8},{"description":244,"name":245,"sourceUrl":246,"tags":247},"Best practices for Remotion - Video creation in React","Remotion Best Practices","https://github.com/digitalsamba/claude-code-video-toolkit/tree/HEAD/.claude/skills/remotion-official",[224,15,248,249,18,250],"react","animation","documentation",{"githubOwner":189,"githubRepo":190,"locale":24,"slug":252,"type":191},"remotion-best-practices",{"extract":254,"llm":255},{"commitSha":196,"license":212},{"promptVersionExtension":169,"promptVersionScoring":170,"score":172,"targetMarket":175,"tier":176},{"repoId":200},{"anyEnrichmentAt":235,"extractAt":236,"githubAt":235,"llmAt":187,"updatedAt":187},{"_creationTime":259,"_id":260,"community":261,"display":262,"identity":273,"providers":277,"relations":286,"workflow":288},1778053968286.4954,"k179afn14fzy4sejmjf82fgqa9867ck6",{"reviewCount":8},{"description":263,"installMethods":264,"name":265,"sourceUrl":266,"tags":267},"Searches arXiv for preprints and academic papers, retrieves abstracts, and filters by topic. Use when the user asks to find research papers, search arXiv, look up preprints, find academic articles in physics, math, CS, biology, statistics, or related fields.",{},"arXiv Search","https://github.com/langchain-ai/deepagents/tree/HEAD/libs/cli/examples/skills/arxiv-search",[268,269,270,271,16,272],"research","data-analytics","arxiv","academic-papers","cli",{"githubOwner":274,"githubRepo":275,"locale":24,"slug":276,"type":191},"langchain-ai","deepagents","arxiv-search",{"extract":278,"llm":280,"smithery":282},{"commitSha":279,"license":212},"b108c71d0c570e16c7050c1eac482e15dc35a5ed",{"promptVersionExtension":169,"promptVersionScoring":170,"score":281,"targetMarket":175,"tier":176},98,{"qualityScore":283,"totalActivations":284,"uniqueUsers":285,"useCount":8,"verified":184},0.7439563,9,8,{"repoId":287},"kd76dna2fvfbnjvzcpd2cwqnyd865xz7",{"anyEnrichmentAt":289,"extractAt":290,"githubAt":291,"llmAt":292,"smitheryAt":289,"updatedAt":292},1778053994907,1778053968286,1778053969344,1778054053159,{"_creationTime":294,"_id":295,"community":296,"display":297,"identity":307,"providers":311,"relations":315,"workflow":317},1778053148350.4656,"k171nxqak0bb4qq89mkfwf02s5867cf6",{"reviewCount":8},{"description":298,"installMethods":299,"name":300,"sourceUrl":301,"tags":302},"Convert PDF files to editable Word documents using pdf2docx",{},"PDF to DOCX Converter","https://github.com/claude-office-skills/skills/tree/HEAD/pdf-to-docx",[303,304,305,306,16],"pdf","docx","conversion","document-processing",{"githubOwner":308,"githubRepo":309,"locale":24,"slug":310,"type":191},"claude-office-skills","skills","pdf-to-docx",{"extract":312,"llm":314},{"commitSha":313,"license":212},"9c4c7d5cd2813a8936bf2c9fdb174ea883b85a11",{"promptVersionExtension":169,"promptVersionScoring":170,"score":281,"targetMarket":175,"tier":176},{"repoId":316},"kd7fw7xbj58qc2z8whrrjptbed8659db",{"anyEnrichmentAt":318,"extractAt":319,"githubAt":318,"llmAt":320,"updatedAt":320},1778053151766,1778053148350,1778053561145,{"_creationTime":322,"_id":323,"community":324,"display":325,"identity":336,"providers":338,"relations":341,"workflow":342},1778053148350.4202,"k17a8yhy4bc401x2yjqa1rvgc9867kxm",{"reviewCount":8},{"description":326,"installMethods":327,"name":328,"sourceUrl":329,"tags":330},"Generate complete presentations with AI - from outline to polished slides",{},"AI Slides","https://github.com/claude-office-skills/skills/tree/HEAD/ai-slides",[331,332,333,334,335,16],"presentation","ai","generation","automatic","mcp",{"githubOwner":308,"githubRepo":309,"locale":24,"slug":337,"type":191},"ai-slides",{"extract":339,"llm":340},{"commitSha":313,"license":212},{"promptVersionExtension":169,"promptVersionScoring":170,"score":281,"targetMarket":175,"tier":176},{"repoId":316},{"anyEnrichmentAt":318,"extractAt":319,"githubAt":318,"llmAt":320,"updatedAt":320},{"_creationTime":344,"_id":345,"community":346,"display":347,"identity":357,"providers":359,"relations":363,"workflow":365},1778053440456.6584,"k17120x7me8p1n30wxpg972esx866b8q",{"reviewCount":8},{"description":348,"installMethods":349,"name":350,"sourceUrl":351,"tags":352},"Transcribe audio to text using ElevenLabs Scribe. Supports batch transcription, realtime streaming from URLs, microphone input, and local files.",{},"ElevenLabs Speech-to-Text","https://github.com/elevenlabs/skills/tree/HEAD/openclaw/elevenlabs-transcribe",[353,354,221,16,355,356],"transcription","audio","realtime","batch",{"githubOwner":221,"githubRepo":309,"locale":24,"slug":358,"type":191},"elevenlabs-transcribe",{"extract":360,"llm":362},{"commitSha":361,"license":212},"b476f0ccf4be0e22b2e77cc39307665425d1472b",{"promptVersionExtension":169,"promptVersionScoring":170,"score":281,"targetMarket":175,"tier":176},{"repoId":364},"kd71z3hz1pg97d1k2d6kaqeqtx864knt",{"anyEnrichmentAt":366,"extractAt":367,"githubAt":366,"llmAt":368,"updatedAt":368},1778053440833,1778053440456,1778053480675,{"_creationTime":370,"_id":371,"community":372,"display":373,"identity":383,"providers":386,"relations":391,"workflow":393},1778053359436.7283,"k173ynpdc9ckbq2dqv7r5xwtqh866w6z",{"reviewCount":8},{"description":374,"installMethods":375,"name":376,"sourceUrl":377,"tags":378},"This skill should be used when the user wants to \"create an agent project\", \"start a new ADK project\", \"build me a new agent\", \"add CI/CD to my project\", \"add deployment\", \"enhance my project\", or \"upgrade my project\". Part of the Google ADK (Agent Development Kit) skills suite. Covers `agents-cli scaffold create`, `scaffold enhance`, and `scaffold upgrade` commands, template options, deployment targets, and the prototype-first workflow. Do NOT use for writing agent code (use google-agents-cli-adk-code) or deployment operations (use google-agents-cli-deploy).",{},"ADK Project Scaffolding Guide","https://github.com/google/agents-cli/tree/HEAD/skills/google-agents-cli-scaffold",[379,380,381,16,272,382],"agents-cli","scaffolding","adk","development-workflow",{"githubOwner":384,"githubRepo":379,"locale":24,"slug":385,"type":191},"google","google-agents-cli-scaffold",{"extract":387,"llm":390},{"commitSha":388,"license":389},"9e2966f509ae8ee8a866cf7ecc6e227209f347ff","Apache-2.0",{"promptVersionExtension":169,"promptVersionScoring":170,"score":281,"targetMarket":175,"tier":176},{"repoId":392},"kd74jrvbwp33xw6azpzkw7r7vs8644t0",{"anyEnrichmentAt":394,"extractAt":395,"githubAt":394,"llmAt":396,"updatedAt":396},1778053359868,1778053359436,1778053387143]