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Found 300 Skills
Comprehensive guide for designing RESTful APIs including resource modeling, versioning strategies, HATEOAS, pagination, filtering, and HTTP best practices
Process multimedia files with FFmpeg (video/audio encoding, conversion, streaming, filtering, hardware acceleration) and ImageMagick (image manipulation, format conversion, batch processing, effects, composition). Use when converting media formats, encoding videos with specific codecs (H.264, H.265, VP9), resizing/cropping images, extracting audio from video, applying filters and effects, optimizing file sizes, creating streaming manifests (HLS/DASH), generating thumbnails, batch processing images, creating composite images, or implementing media processing pipelines. Supports 100+ formats, hardware acceleration (NVENC, QSV), and complex filtergraphs.
Extracts specific fields from JSON files efficiently using jq instead of reading entire files, saving 80-95% context. Use this skill when querying JSON files, filtering/transforming data, or getting specific field(s) from large JSON files
REST API design patterns including resource naming, status codes, pagination, filtering, error responses, versioning, and rate limiting for production APIs.
Amazon Movers & Shakers data acquisition tool. This skill is used when users need to find hot products with recently soaring sales on Amazon, discover bestseller trends, and obtain the soaring list product list. It supports filtering by category, outputs data such as basic product information, price, ranking trend, etc., providing original market data for Temu product selection.
WeCom to-do list query skill, which supports filtering by creation time and reminder time, as well as pagination. It is applicable to scenarios where users need to browse the to-do overview, such as when they say "Check my to-do list", "What to-dos do I have", "What are my to-dos this week", "What to-dos are there recently", "Check my to-dos", "List all to-dos", etc. Note: This skill only returns to-do summary information (excluding content and assignees). If you need complete details, please use it together with wecomcli-get-todo-detail.
Verify and validate AI output before it reaches users. Use when you need guardrails, output validation, safety checks, content filtering, fact-checking AI responses, catching hallucinations, preventing bad outputs, quality gates, or ensuring AI responses meet your standards before shipping them. Covers DSPy assertions, verification patterns, and generate-then-filter pipelines.
Implement the Syncfusion Angular MultiSelect Dropdown component (ejs-multiselect) for multi-value selection with checkbox support, tag/chip inputs, and searchable lists. Use this when building multi-select dropdowns, checkbox selection lists, or tag-based input fields. This skill covers filtering, CheckBoxSelection mode, cascading dropdowns, and data binding for the MultiSelect component.
Performs quality control on single-cell RNA-seq data (.h5ad or .h5 files) using scverse best practices with MAD-based filtering and comprehensive visualizations. Use when users request QC analysis, filtering low-quality cells, assessing data quality, or following scverse/scanpy best practices for single-cell analysis.
Query TradingView screener data for HK, A-share, A-share ETF, and US symbols with deepentropy/tvscreener. Use for stock lookup, technical indicators (price/change/RSI/MACD/volume), symbol filtering, and custom field/filter-based market queries.
Generate styled word clouds from text with custom shapes, colors, fonts, and stopword filtering. Supports PNG/SVG export and frequency dictionaries.
Repository packaging for AI/LLM analysis. Capabilities: pack repos into single files, generate AI-friendly context, codebase snapshots, security audit prep, filter/exclude patterns, token counting, multiple output formats. Actions: pack, generate, export, analyze repositories for LLMs. Keywords: Repomix, repository packaging, LLM context, AI analysis, codebase snapshot, Claude context, ChatGPT context, Gemini context, code packaging, token count, file filtering, security audit, third-party library analysis, context window, single file output. Use when: packaging codebases for AI, generating LLM context, creating codebase snapshots, analyzing third-party libraries, preparing security audits, feeding repos to Claude/ChatGPT/Gemini.