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Found 1,036 Skills
Annotates codebases with dimensional analysis comments documenting units, dimensions, and decimal scaling. Use when someone asks to annotate units in a codebase, perform a dimensional analysis, or find vulnerabilities in a DeFi protocol, offchain code, or other blockchain-related codebase with arithmetic. Prevents dimensional mismatches and catches formula bugs early.
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).
Transfer app data between platforms using AppMigrationKit. Use when implementing one-time data migration from Android or other platforms to iOS, managing cross-platform transfer sessions with AppMigrationExtension, packaging and archiving user data for export, importing resources on the destination device, tracking transfer progress, handling migration errors, or building onboarding flows that import existing user data.
When the user wants help writing opening lines, hooks, or first sentences that grab attention. Also use when the user mentions 'hook,' 'opening line,' 'first line,' 'scroll stopper,' 'attention grabber,' 'headline,' 'how to start my post,' or 'nobody reads past my first line.' Can be used standalone or invoked by other creation skills. For writing full posts, see post-writer-sms. For threads, see thread-writer-sms.
A natural language workflow for converting literary works (novels, stories, scripts, one-sentence concepts, etc.) into film and video content, which converts novel content into complete videos by orchestrating multiple skills in sequence. This skill is used when users need to convert novels, stories or other literary works into videos.
Elevate a project-local skill to the shared ai-skills repo. Use when you want a project skill available in other repos.
Query and analyze business data in NocoBase via MCP. Use when users want current counts, grouped breakdowns, owner/source distributions, or business summaries across collections, with main data source first and fallback discovery to other enabled data sources.
In-process ClickHouse SQL engine for Python — run ClickHouse SQL queries directly on local files, remote databases, and cloud storage without a server. Use when the user wants to write SQL queries against Parquet/CSV/ JSON files, use ClickHouse table functions (mysql(), s3(), postgresql(), iceberg(), deltaLake() etc.), build stateful analytical pipelines with Session, use parametrized queries, window functions, or other advanced ClickHouse SQL features. Also use when the user explicitly mentions chdb.query(), ClickHouse SQL syntax, or wants cross-source SQL joins. Do NOT use for pandas-style DataFrame operations — use chdb-datastore instead.
OpenTelemetry with Grafana stack. Covers OTel SDK instrumentation for Go/Java/Python/Node.js/.NET, OTLP protocol and endpoint configuration, sending telemetry to Grafana Cloud via OTLP endpoint, Grafana Alloy as OTel collector, sampling strategies, Kubernetes OTel Operator, and migration from other observability tools. Use when instrumenting apps with OTel, configuring OTLP endpoints, setting up collectors, or migrating to OpenTelemetry.