Skill UI

This guide provides a robust implementation for handling asynchronous webhooks from ElevenLabs. It covers the critical steps of receiving POST notifications (such as transcription completion, post-call audio, and failure events), performing secure HMAC-SHA256 signature verification, and routing the event data to specific processing handlers. Ideal for integrating ElevenLabs into conversational AI pipelines, ensuring data integrity and reliable background processing.

A comprehensive evaluation suite designed to benchmark the performance of Large Language Models (LLM) and Vision-Language Models (VLM) specifically for home security applications. It covers 143 diverse tests across 16 critical domains, including tool use, prompt injection resistance, contextual reasoning, alert triage, and detailed scene analysis, ensuring robustness for smart home AI systems.

This benchmark evaluates Vision-Language Models (VLMs) on detecting potential safety hazards within indoor environments. It uses static camera frames, simulating real-world fixed security camera monitoring. The test covers 40 scenarios across 5 critical categories, including fire/smoke, electrical risks, trips/falls, child safety, and falling objects, providing a rigorous measure of VLM's practical safety inspection capability.

Master the complexities of building robust Retrieval Augmented Generation (RAG) pipelines using LangChain. This guide addresses common pitfalls in vector search, such as score semantics differences (L2 vs. Cosine), embedding dimension mismatches, and chunking issues for code/Markdown. Learn best practices for selecting between FAISS, Pinecone, Chroma, and PGVector, normalizing scores, and implementing hybrid keyword+vector search for maximum retrieval quality.

This harness provides comprehensive, reproducible evaluation pipelines for complex LLM chains and agents (LangChain/LangGraph 1.0). It integrates golden dataset management, LangSmith evaluation, RAGAS metrics, deepeval LLM-as-judge, and structured agent trajectory analysis. Use it when establishing quality benchmarks for new chains, diagnosing performance regressions after model switches, or implementing CI/CD gates to prevent quality drops.

This skill integrates LangChain 1.0 and LangGraph 1.0 into standard OpenTelemetry (OTEL) backends (e.g., Jaeger, Honeycomb, Tempo). It solves critical observability gaps by ensuring correct prompt content capture, propagating spans across complex subgraphs, and providing five LLM-specific Service Level Objectives (SLOs) like latency and cost. Ideal for multi-tenant, compliance-sensitive, or existing OTEL stack environments where LangSmith is unsuitable.

A comprehensive skill for generating high-quality AI images and videos using advanced models like Seedance 2.0, Kling 3.0, and Midjourney. It supports diverse workflows including text-to-image, image-to-video, and video continuation. The system handles asynchronous generation, robust delivery, and multi-channel integration (e.g., Feishu, Slack), making it ideal for creative content production and automated media workflows.

This is an all-in-one command-line tool for generating and editing images using the full Nano Banana model family. Users can select the optimal model—Gemini 3.1 Flash for balanced performance, Gemini 3 Pro for high-quality output, or Gemini 2.5 Flash for speed—to suit their needs. Key features include text-to-image generation, precise single image editing, and multi-image collage composition, making it versatile for creative and technical workflows.

A comprehensive offensive checklist for assessing the security and robustness of AI and Large Language Model (LLM) applications. It covers advanced adversarial techniques such as prompt injection, jailbreaking, model extraction, data poisoning, and analyzing system vulnerabilities across components. Essential for red-teaming and security assessment.

This skill orchestrates the entire patent drafting lifecycle, guiding users from an initial invention concept to legally formatted filing documents. It manages critical steps such as prior art search, claims design, specification writing, and jurisdiction-specific formatting. Supports Invention and Utility Models across CN, US, and EP jurisdictions.

Simulates a comprehensive, multi-round patent examiner review process. It analyzes patent claims and specifications against international standards (USPTO, CNIPA, EPO) to assess novelty, non-obviousness, claim clarity, and enablement. The tool provides detailed office actions, critical feedback, and iterative improvement rounds to maximize patentability.

This skill provides comprehensive analysis and improvement suggestions for plugin prompts, skill definitions, and command instructions. It evaluates content across five dimensions—clarity, safety, effectiveness, completeness, and conciseness—providing a detailed score card and concrete, actionable rewrites to ensure compliance and optimal AI performance.