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Found 1,835 Skills
Designs git workflows covering branching strategies, trunk-based development, stacked changes, conventional commits, CI/CD pipelines, and repository hygiene. Use when setting up branching models, writing commit messages, configuring GitHub Actions, managing stacked PRs, cleaning stale branches, creating issue templates, or recovering lost commits.
Build production-ready systems with stability patterns: circuit breakers, bulkheads, timeouts, and retry logic. Use when the user mentions "production outage", "circuit breaker", "timeout strategy", "deployment pipeline", or "chaos engineering". Covers capacity planning, health checks, and anti-fragility patterns. For data systems, see ddia-systems. For system architecture, see system-design.
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.
Creates Robot Framework test cases for creating and executing SnapLogic triggered tasks. Use when the user wants to create triggered tasks for on-demand pipeline execution, execute triggered tasks with parameters, or wants to see triggered task test case examples.
Orchestrates test planning pipeline (research → manual → auto tests). Coordinates ln-521, ln-522, ln-523. Invoked by ln-500-story-quality-gate.
Blender to web export workflows for 3D models and animations. Use this skill when exporting Blender models to glTF for web, optimizing 3D assets for Three.js or Babylon.js, batch processing models with Python scripts, automating Blender workflows, or creating web-ready 3D pipelines. Triggers on tasks involving Blender glTF export, bpy scripting, 3D asset optimization, model compression, texture baking, or Blender automation. Exports models for threejs-webgl, react-three-fiber, and babylonjs-engine skills.
Comprehensive prompt and context engineering for any AI system. Four modes: (1) Craft new prompts from scratch, (2) Analyze existing prompts with diagnostic scoring and optional improvement, (3) Convert prompts between model families (Claude/GPT/Gemini/Llama), (4) Evaluate prompts with test suites and rubrics. Adapts all recommendations to model class (instruction-following vs reasoning). Validates findings against current documentation. Use for system prompts, agent prompts, RAG pipelines, tool definitions, or any LLM context design. NOT for running prompts, generating content, or building agents.
GitHub Actions workflow patterns for React Native iOS simulator and Android emulator cloud builds with downloadable artifacts. Use when setting up CI build pipelines or downloading GitHub Actions artifacts via gh CLI and GitHub API.
Deterministic API endpoint validation with structured pass/fail reporting. Use when endpoints need smoke testing, health checks are required before deployment, or CI/CD pipelines need HTTP validation gates. Use for "validate endpoints", "check api health", "api smoke test", or "are endpoints working". Do NOT use for load testing, browser testing, full integration suites, or OAuth/complex authentication flows.
Expert knowledge for Azure Machine Learning development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using Azure ML pipelines, AutoML, managed online/batch endpoints, prompt flow, or MLflow deployments, and other Azure Machine Learning related development tasks. Not for Azure Databricks (use azure-databricks), Azure Synapse Analytics (use azure-synapse-analytics), Azure HDInsight (use azure-hdinsight), Azure Data Science Virtual Machines (use azure-data-science-vm).
Use when the user needs ML pipelines, statistical analysis, data preprocessing, feature engineering, model selection, experiment tracking, or data visualization. Triggers: dataset exploration, model training, feature engineering, hyperparameter tuning, experiment tracking setup, statistical hypothesis testing, visualization creation.
Create security architecture diagrams using PlantUML syntax with identity, encryption, firewall, and compliance stencil icons. Best for IAM flows, zero-trust architectures, encryption pipelines, compliance auditing, and threat detection. NOT for general cloud infra (use cloud skill) or simple flowcharts (use mermaid).