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Expert knowledge of the libvlc C API (3.x and 4.x), the multimedia framework behind VLC media player. Use when helping with LibVLC or LibVLCSharp for media playback, streaming, or transcoding. USE FOR: LibVLC Skill implementation, review, migration, debugging, or documentation work. DO NOT USE FOR: unrelated stacks; generic tasks that do not need this specific guidance. INVOKES: inspect the repository context, edit targeted files, and run relevant build, test, lint, or validation commands when changes are made.

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Guides conversion of a pre-.NET 8 Blazor Server app into a .NET 8+ Blazor Web App. USE FOR: migrating apps that use AddServerSideBlazor and MapBlazorHub to the AddRazorComponents/MapRazorComponents model, converting _Host.cshtml to an App.razor root component, replacing blazor.server.js with blazor.web.js, migrating CascadingAuthenticationState to a service, adopting new Blazor Web App features like enhanced navigation and streaming rendering. DO NOT USE FOR: apps that are already Blazor Web Apps (already use AddRazorComponents and MapRazorComponents), Blazor WebAssembly or hosted Blazor WebAssembly apps (different migration path), apps that should stay on the Blazor Server hosting model without converting, or apps still targeting .NET Framework.

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Build or review gRPC services and clients in .NET. USE FOR: ASP.NET Core gRPC, protobuf contracts, unary or streaming RPC, gRPC client factory, interceptors, deadlines, cancellation, channel reuse, backend service integration. DO NOT USE FOR: broad browser-facing APIs without gRPC-Web tradeoff review, SignalR realtime hubs, plain REST APIs. INVOKES: dotnet build/test and focused service or client smoke checks when code changes.

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Generate HeyGen presenter videos via the v3 Video Agent pipeline — handles Frame Check (aspect ratio correction), prompt engineering, avatar resolution, and voice selection. Required for any HeyGen video generation. Replaces deprecated endpoints with v3. Use when: (1) generating any HeyGen video (via API or otherwise), (2) sending a personalized video message (outreach, update, announcement, pitch, knowledge), (3) creating a HeyGen presenter-led explainer, tutorial, or product demo with a human face, (4) "make a video of me saying...", "send a video to my leads", "record an update for my team", "create a video pitch", "make a loom-style message", "I want to appear in this video", "generate a HeyGen video", "make a talking head video". Accepts avatar_id from heygen-avatar for identity-first HeyGen videos, or uses a stock presenter. Returns video share URL + HeyGen session URL for iteration. Chain signal: when the user wants to create/design an avatar AND make a video in the same request, run heygen-avatar first, then return here. Conjunctions to watch: "and then", "and immediately", "first...then", "X and make a video", "design [presenter] and record" = always CHAIN. If the user provides a photo AND wants a video, route to heygen-avatar first. NOT for: avatar creation or identity setup (use heygen-avatar first), cinematic footage or b-roll without a presenter, translating videos, TTS-only, or streaming avatars.

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Entrypoint for managing Volcengine Flink (based on Apache Flink) workloads. Use it for developing and deploying streaming and batch jobs, diagnosing real-time issues (e.g., backpressure, checkpoint failures, OOM), troubleshooting resources, and performing SRE actions (stop/start/restart/scale/config changes). It intelligently routes requests to four specialized sub-skills and leverages flink-mcp for tool execution.

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Volcengine VOD audio and video processing tools skill. Use when users need VOD-based media processing or editing: upload local/URL media, stitch videos, trim clips, flip frames, change playback speed, create image-to-video, compose audio/video, extract audio, mix audio, separate vocals/accompaniment, denoise audio, enhance quality, AI super-resolution, frame interpolation, ASR speech-to-text, OCR text extraction, subtitle removal, subtitle embedding, scene slicing, portrait/green-screen matting, highlight extraction, comic style transfer, video translation, drama recap narration, drama script restoration, media info lookup, or playback URL retrieval. The skill submits async VOD jobs, polls task status, and returns generated output links. Not for pure text generation, real-time streaming, or source-free generative video creation.

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Comprehensive Polymarket skill covering prediction markets, API, trading, market data, and real-time WebSocket data streaming. Build applications with Polymarket services, monitor live trades, and integrate market predictions.

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Cryptofeed - Real-time cryptocurrency market data feeds from 40+ exchanges. WebSocket streaming, normalized data, order books, trades, tickers. Python library for algorithmic trading and market data analysis.

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Real-time Solana transaction and account streaming via Yellowstone gRPC (Geyser plugin)

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Self-hosted Solana DEX aggregator by SolanaTracker — multi-hop routing across 25+ DEXes, WebSocket streaming, Yellowstone Jet TPU submission, no rate limits

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Pre-execution Solana transaction streaming via Jito ShredStream, Shyft RabbitStream, and Triton Deshred

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Builds AI agents on the Convex agent component: threads, messages, tools that call queries and mutations, streaming, RAG with vector search, and workflows for multi step jobs. Use when adding a chat assistant, tool calling agent, or retrieval feature to a Convex app.

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Adds HTTP endpoints in convex/http.ts: webhook receivers with signature checks, REST style routes, CORS, auth headers, streaming responses, and file uploads over HTTP. Use when integrating Stripe, Clerk, Resend, or any service that calls back into the app, or when a client needs a plain HTTP API.

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Stop and consult this skill whenever your response would include specific facts about Anthropic's products. Covers: Claude Code (how to install, Node.js requirements, platform/OS support, MCP server integration, configuration), Claude API (function calling/tool use, batch processing, SDK usage, rate limits, pricing, models, streaming), and Claude.ai (Pro vs Team vs Enterprise plans, feature limits). Trigger this even for coding tasks that use the Anthropic SDK, content creation mentioning Claude capabilities or pricing, or LLM provider comparisons. Any time you would otherwise rely on memory for Anthropic product details, verify here instead — your training data may be outdated or wrong.

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Stream-JSON chaining for multi-agent pipelines, data transformation, and sequential workflows

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Comprehensive best practices for robot perception systems covering cameras, LiDARs, depth sensors, IMUs, and multi-sensor setups. Use this skill when working with RGB image processing, depth maps, point clouds, sensor calibration (intrinsic, extrinsic, hand-eye), object detection, semantic segmentation, 3D reconstruction, visual servoing, or perception pipeline optimization. Trigger whenever the user mentions OpenCV, Open3D, PCL, RealSense, ZED, OAK-D, camera calibration, AprilTags, ArUco markers, stereo vision, RGBD, point cloud filtering, ICP registration, coordinate transforms, camera intrinsics, distortion correction, image undistortion, sensor streaming, frame synchronization, or any computer vision task in a robotics context. Also covers multi-camera rigs, time synchronization across sensors, perception latency budgets, and production deployment of perception pipelines.

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Stream-JSON chaining for multi-agent pipelines, data transformation, and sequential workflows

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Databricks AI Runtime, the `databricks air` CLI commands for submitting and managing GPU training workloads on Databricks serverless compute. Use for: writing and submitting `databricks air` workload YAML, passing hyperparameters and secrets, checking run status, listing/cancelling runs, streaming a run's logs and watching its progress, custom Docker image setup, and environment configuration.

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Apache Iceberg tables on Databricks — Managed Iceberg tables, External Iceberg Reads (fka Uniform), Compatibility Mode, Iceberg REST Catalog (IRC), Iceberg v3, Snowflake interop, PyIceberg, OSS Spark, external engine access and credential vending. Use when creating Iceberg tables, enabling External Iceberg Reads (uniform) on Delta tables (including Streaming Tables and Materialized Views via compatibility mode), configuring external engines to read Databricks tables via Unity Catalog IRC, integrating with Snowflake catalog to read Foreign Iceberg tables

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Develop Lakeflow Spark Declarative Pipelines (formerly Delta Live Tables) on Databricks. Use when building batch or streaming data pipelines with Python or SQL, including Auto CDC from event streams or periodic complete snapshots. Invoke BEFORE starting implementation.

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Train ML models on Databricks. Use for: classification/regression/deep-learning (XGBoost, scikit-learn, LightGBM, PyTorch) with Optuna, @prod/@challenger aliases, batch scoring (spark_udf for plain models, fe.score_batch for feature-store-backed), custom PyFunc, custom ResponsesAgent (LangGraph + UC Function/Vector Search); UC feature tables + FeatureLookup + point-in-time joins + Lakebase online store; declarative Feature Views (create_feature, DeltaTableSource, RollingWindow/SlidingWindow/TumblingWindow, materialize_features, streaming Kafka features). NOT for: endpoint ops (databricks-model-serving), MLflow evaluation (databricks-mlflow-evaluation).

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Build custom Python data sources for Apache Spark using the PySpark DataSource API — batch and streaming readers/writers for external systems. Use this skill whenever someone wants to connect Spark to an external system (database, API, message queue, custom protocol), build a Spark connector or plugin in Python, implement a DataSourceReader or DataSourceWriter, pull data from or push data to a system via Spark, or work with the PySpark DataSource API in any way. Even if they just say "read from X in Spark" or "write DataFrame to Y" and there's no native connector, this skill applies.

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Online (incremental) covariance, correlation, and precision estimation in Python — the streaming complement to sklearn.covariance. Use when code needs a covariance/correlation matrix updated per observation, recomputes np.cov/np.corrcoef in a rolling loop, must judge or compare covariance estimates, or proposes a new covariance methodology. Points to task-specific skills.

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Routes official FlashVSR diffusion-based streaming video super-resolution setup, model preparation, and CUDA inference for v1 and v1.1.

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