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Found 2,691 Skills
Use this skill to interact with Moorcheh, the Universal Memory Layer for Agentic AI. Provides semantic search with ITS (Information-Theoretic Scoring), namespace management, text and vector data operations, and AI-powered answer generation (RAG). Use when building applications that need semantic search, knowledge bases, document Q&A, AI memory systems, or retrieval-augmented generation.
Generate clear, conventional commit messages from staged changes. Use when the user asks to commit or needs a commit message.
Expert knowledge for Azure AI Custom Vision development including best practices, decision making, limits & quotas, security, integrations & coding patterns, and deployment. Use when exporting Custom Vision models, calling prediction APIs, using ONNX/TensorFlow, managing CMK/RBAC, or Smart Labeler, and other Azure AI Custom Vision related development tasks. Not for Azure AI Vision (use azure-ai-vision), Azure AI services (use microsoft-foundry-tools), Azure Machine Learning (use azure-machine-learning), Azure AI Foundry Local (use microsoft-foundry-local).
Expert knowledge for Microsoft Foundry Tools (aka Azure AI services, Azure Cognitive Services) development including best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using Content Understanding analyzers, Content Moderator APIs, Foundry containers, VNet/Key Vault security, or Entra auth, and other Microsoft Foundry Tools related development tasks. Not for Microsoft Foundry (use microsoft-foundry), Microsoft Foundry Classic (use microsoft-foundry-classic), Microsoft Foundry Local (use microsoft-foundry-local).
Expert knowledge for Azure AI Video Indexer development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using Video Indexer APIs/widgets, live camera indexing, custom speech/brand models, or Azure OpenAI integrations, and other Azure AI Video Indexer related development tasks. Not for Azure AI services (use microsoft-foundry-tools), Azure AI Vision (use azure-ai-vision).
Expert knowledge for Azure AI Document Intelligence development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using AnalyzeDocument/Markdown APIs, custom models, containers/Docker, SAS/managed identity, or VNets, and other Azure AI Document Intelligence related development tasks. Not for Azure AI services (use microsoft-foundry-tools), Azure AI Search (use azure-cognitive-search), Azure AI Language (use azure-language-service), Azure AI Immersive Reader (use azure-immersive-reader).
Attach judges to AI Config variations for automatic LLM-as-a-judge evaluation. Create custom judges, configure sampling rates, and monitor quality scores.
Configure AI Config targeting rules to control which variations serve to different users. Enable percentage rollouts, attribute-based rules, segment targeting, and guarded rollouts.
Implements and debugs browser Language Detector API integrations in JavaScript or TypeScript web apps. Use when adding LanguageDetector support checks, availability and model download flows, session creation, detect() calls, input-usage measurement, permissions-policy handling, or compatibility fallbacks for built-in language detection. Don't use for server-side language detection SDKs, cloud translation services, or generic NLP pipelines.
Diagnose and fix bugs with root-cause analysis and verification. Use when you have a concrete issue report, failing behavior, runtime error, or test regression that should be resolved safely. For ambiguous, high-risk, or broad-scope issues, stop and route to write-plan first.
Review current uncommitted git changes with full file context and produce a structured report with severity levels, actionable fixes, and an approval verdict.
Enterprise skill for iOS production error observability and logging (iOS 15+, Swift 5.5+). Use this skill when writing or reviewing error handling code, adding logging to iOS apps, replacing print() with os.Logger, configuring crash reporting SDKs (Sentry, Crashlytics, PostHog), fixing silent error patterns (try?, Task {} swallowing errors, Combine pipelines dying), adding privacy annotations to logs, integrating MetricKit, implementing retry logic with observability, handling errors in SwiftUI .task {} modifiers, or auditing catch blocks for proper error reporting. Use this skill any time someone writes a catch block, uses try?, creates a Task {}, sets up error handling, or mentions logging, crash reporting, or error tracking in an iOS context — even if they just say 'add error handling' or 'why is this failing silently.'