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Found 130 Skills
Find and download virtually any digital resource from the internet — ebooks, academic papers, movies, TV shows, music, software, images, fonts, courses, and more. Covers both English and Chinese internet ecosystems. Includes CLI tool workflows (yt-dlp, aria2, gallery-dl, spotdl), resource site directories, cloud drive search engines (百度/阿里/夸克网盘搜索), and search techniques (Google dorks). Use when the user wants to: (1) download a video, audio, or media from a URL, (2) find and download an ebook or academic paper, (3) find and download software, (4) search for any digital resource, (5) batch download images or media from a gallery/site, (6) download torrents or magnet links, (7) find free stock assets (images, video, audio, fonts), (8) search Chinese cloud drives for resources, or (9) any task involving finding or downloading digital content from the internet.
Use when asked to scan, decode, read, or extract data from QR codes or barcodes in images.
Remove backgrounds from images using segmentation. Support for color-based, edge detection, and AI-assisted removal methods. Batch processing available.
Colorize black and white photos using each::sense AI. Bring old family portraits, historical images, vintage photographs, and archival footage to life with intelligent, context-aware colorization.
Production-grade FFmpeg video/audio processing. Convert, compress, trim, merge, resize, and extract audio from media files with progress tracking, comprehensive error handling, and safety limits.
Neo4j Python Driver v6 — driver lifecycle, execute_query, managed and explicit transactions, async (AsyncGraphDatabase), result handling, data type mapping, error handling, UNWIND batching, connection pool tuning, and causal consistency. Use when writing Python code that connects to Neo4j via GraphDatabase.driver, execute_query, execute_read, execute_write, AsyncGraphDatabase, neo4j.Result, or RoutingControl. Package name is `neo4j` (not neo4j-driver) since v6. Python >=3.10 required. Does NOT handle Cypher query authoring — use neo4j-cypher-skill. Does NOT cover driver upgrades or breaking changes — use neo4j-migration-skill. Does NOT cover GraphRAG pipelines (neo4j-graphrag package) — use neo4j-graphrag-skill.
Add multiple functional specs to the ***functional specs*** section of a ***plain spec file in a single batch. Use whenever more than one new functional spec is being added — whether the user explicitly asks, or another skill/workflow (e.g. forge-plain, add-feature) needs to author several specs in one pass. Bulk-writing or hand-authoring functional specs without invoking this skill is forbidden; for adding a single spec, use add-functional-spec instead.
Upload one or many videos to YouTube. Use when the user wants to "上传到 YouTube", "发 YouTube", "批量上传", "upload to YouTube", "post videos to YouTube", or to publish a finished `final/` directory of MP4s. Reads per-video metadata (title / description / tags) from a sibling `UPLOAD_META.md` file when present (the user's standard markdown format), or from command-line flags. Survives behind a SOCKS/HTTP proxy by using `requests` directly for the resumable upload (the stock `google-api-python-client` MediaFileUpload stalls under this user's proxy setup).
Retrieve activity history (calls, emails, notes, meetings, tasks) for a CRM record and assemble pre-call briefs.
Find a specific CRM record by ID, email, domain, or name fragment, and traverse associations for the full account picture.
Complete subtitle and caption system for FFmpeg 7.1 LTS and 8.0.1 (latest stable, released 2025-11-20). PROACTIVELY activate for: (1) Burning subtitles (hardcoding SRT/ASS/VTT), (2) Adding soft subtitle tracks, (3) Extracting subtitles from video, (4) Subtitle format conversion, (5) Styled captions (font, color, outline, shadow), (6) Subtitle positioning and alignment, (7) CEA-608/708 closed captions, (8) Text overlays with drawtext, (9) Whisper AI automatic transcription (FFmpeg 8.0+ with VAD, multi-language, GPU), (10) Batch subtitle processing. Provides: Format reference tables, styling parameter guide, position alignment charts, Whisper model comparison, VAD configuration, dynamic text examples, accessibility best practices. Ensures: Professional captions with proper styling and accessibility compliance.
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.