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Found 346 Skills
Build custom dropdown/select/autocomplete/multiselect components using Mantine's Combobox primitives. Use this skill when: (1) creating a new custom select-like component with Combobox primitives, (2) building a searchable dropdown, (3) implementing a multi-select or tags input variant, (4) customizing option rendering, (5) adding custom filtering logic, or (6) any task involving useCombobox, Combobox.Target, Combobox.Option, or Combobox.Dropdown.
Guides development with SAP AI Core and SAP AI Launchpad for enterprise AI/ML workloads on SAP BTP. Use when: deploying generative AI models (GPT, Claude, Gemini, Llama), building orchestration workflows with templating/filtering/grounding, implementing RAG with vector databases, managing ML training pipelines with Argo Workflows, configuring content filtering and data masking for PII protection, using the Generative AI Hub for prompt experimentation, or integrating AI capabilities into SAP applications. Covers service plans (Free/Standard/Extended), model providers (Azure OpenAI, AWS Bedrock, GCP Vertex AI, Mistral, IBM), orchestration modules, embeddings, tool calling, and structured outputs.
Hookdeck Event Gateway — webhook infrastructure that replaces your queue. Use when receiving webhooks and need guaranteed delivery, automatic retries, replay, rate limiting, filtering, or observability. Eliminates the need for your own message queue for webhook processing.
Crypto news search, AI ratings, trading signals, and real-time updates via the OpenNews 6551 API. Supports keyword search, coin filtering, source filtering, AI score ranking, and WebSocket live feeds.
Repository packaging for AI/LLM analysis. Capabilities: pack repos into single files, generate AI-friendly context, codebase snapshots, security audit prep, filter/exclude patterns, token counting, multiple output formats. Actions: pack, generate, export, analyze repositories for LLMs. Keywords: Repomix, repository packaging, LLM context, AI analysis, codebase snapshot, Claude context, ChatGPT context, Gemini context, code packaging, token count, file filtering, security audit, third-party library analysis, context window, single file output. Use when: packaging codebases for AI, generating LLM context, creating codebase snapshots, analyzing third-party libraries, preparing security audits, feeding repos to Claude/ChatGPT/Gemini.
Credit risk data cleaning and variable screening pipeline for pre-loan modeling. Use when working with raw credit data that needs quality assessment, missing value analysis, or variable selection before modeling. it covers data loading and formatting, abnormal period filtering, missing rate calculation, high-missing variable removal,low-IV variable filtering, high-PSI variable removal, Null Importance denoising, high-correlation variable removal, and cleaning report generation. Applicable scenarios arecredit risk data cleaning, variable screening, pre-loan modeling preprocessing.
Meta's 7-8B specialized moderation model for LLM input/output filtering. 6 safety categories - violence/hate, sexual content, weapons, substances, self-harm, criminal planning. 94-95% accuracy. Deploy with vLLM, HuggingFace, Sagemaker. Integrates with NeMo Guardrails.
Manage MCP servers - discover, analyze, execute tools/prompts/resources. Use for MCP integrations, capability discovery, tool filtering, programmatic execution, or encountering context bloat, server configuration, tool execution errors.
Create production-quality Django REST Framework APIs using Clean Architecture and SOLID principles. Covers layered architecture (views, use cases, services, models), query optimization (N+1 prevention), pagination/filtering, JWT authentication, permissions, and production deployment. Use when building new Django APIs, implementing domain-driven design, optimizing queries, or configuring authentication. Applies Python 3.12+ and Django 5+ patterns.
Write SQL, TypeScript, and dynamic table transforms for Goldsky Turbo pipelines. Use this skill for: decoding EVM event logs with _gs_log_decode (requires ABI) or transaction inputs with _gs_tx_decode, filtering and casting blockchain data in SQL, combining multiple decoded event types into one table with UNION ALL, writing TypeScript/WASM transforms using the invoke(data) function signature, setting up dynamic lookup tables to filter transfers by a wallet list you update at runtime (dynamic_table_check), chaining SQL and TypeScript steps together, or debugging null values in decoded fields. For full pipeline YAML structure, use /turbo-pipelines instead. For building an entire pipeline end-to-end, use /turbo-builder instead.
OpenTelemetry Transformation Language (OTTL) expert. Use when writing or debugging OTTL expressions for any OpenTelemetry Collector component that supports OTTL (processors, connectors, receivers, exporters). Triggers on tasks involving telemetry transformation, filtering, attribute manipulation, data redaction, sampling policies, routing, or Collector configuration. Covers syntax, contexts, functions, error handling, and performance.
YAML querying, filtering, and transformation with yq command-line tool. Use when working with YAML files, parsing YAML configuration, modifying Kubernetes manifests, GitHub Actions workflows, or transforming YAML structures.