Your agent can do more. Find the skill that makes it happen.
Find your next superpower If you are an agent, refer to our llms.txt for full access.Manage VSCode/Cursor configuration in this dotfiles repository. Use when working with settings.json, keybindings.json, or tasks.json files, or when asked about VSCode/Cursor configuration structure.
Provides guidelines for contributing commands to VS Code extensions. Covers naming conventions, visibility, localization, and relevant attributes using extension development practices and libraries.
Provides guidance for localizing VS Code extensions. Follows VS Code extension development guidelines, libraries, and recommended practices.
Guides changes to the extension UI, commands, and configuration logic. Covers rebuilding the extension, packaging it, and reinstalling its VSIX in VS Code.
Uses the VSS agent's video_understanding tool to answer new visual questions about recorded video. Excludes questions answerable from metadata, previous tool output, or search hits.
Covers standalone RT-VLM deployment and API operations for uploads, captions, streams, chat completions, and Kafka. Excludes VSS profile deployment and video-search ingestion.
Handles deployment, execution, debugging, teardown, and REST API access for RTVI-CV. Includes stream management and health checks, while excluding VLM, embedding, and analytics services.
Runs RTVI-CV-3D in MV3DT mode with per-camera DeepStream perception and BEV Fusion. Supports sample data, custom videos, and RTSP streams, and invokes video calibration when calibration is missing.
Manages VSS profiles including base, search, lvs, warehouse, and edge. Covers configuration and deployment through verification, debugging, and teardown; standalone microservices use separate deployment skills.
Covers VSS 3.2 GA RT-Embed deployment with Docker Compose, GPU and storage prerequisites, operations, and teardown. Includes uploads, text and video embeddings, RTSP streams, health metrics, Redis/Kafka/OTel integration, and common failures.
Generates calibration using AutoMagicCalib with local MP4 files, RTSP streams, or the bundled sample dataset. Supports deploying vss-auto-calibration and excludes other calibration methods and runtime analytics.
Generates analysis reports using per-clip VLM processing in Mode A or incident-range video analytics in Mode B. Excludes standalone video summaries, real-time alerts, and ad hoc questions.
Skills give your agent reusable instructions for a specific job. Pick one, read what it does, and bring it into your workflow.
A name only tells half the story. Search the full description and instructions to find the right fit.
Read the skill, visit its source, and see exactly what you’re adding to your agent.
Copy the install command from a skill page and run it in your project.
npx skillycli add owner/repo --skill name