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Found 40 Skills
One-time setup that gathers design context for your project and saves it to your AI config file. Run once to establish persistent design guidelines.
Generate app icons for your React Native Expo app with iOS 26 support
Guide for setting up AI configuration in your application. Helps you choose between agent vs completion mode, select the right approach for your stack, and create AI Configs that make sense for your use case.
Guide for experimenting with AI configurations. Helps you test different models, prompts, and parameters to find what works best through systematic experimentation.
Attach judges to AI Config variations for automatic LLM-as-a-judge evaluation. Create custom judges, configure sampling rates, and monitor quality scores.
Configure code chunking in GrepAI. Use this skill to optimize how code is split for embedding.
Migrate an application with hardcoded LLM prompts to a full LaunchDarkly AI Configs implementation in five stages: extract prompts, wrap in the AI SDK, add tools, add tracking, add evals/judges. Use when the user wants to externalize model/prompt configuration, move from direct provider calls (OpenAI, Anthropic, Bedrock, Gemini) to a managed AI Config, or stage a full hardcoded-to-LaunchDarkly migration.
Configure OpenAI as embedding provider for GrepAI. Use this skill for high-quality cloud embeddings.
Configure PostgreSQL with pgvector for GrepAI. Use this skill for team environments and large codebases.
Create, track, retrieve, update, and delete custom business metrics for AI Configs. Covers full lifecycle: define metric kinds via API, emit events via SDK, and query results.
Expert guide for creating GitHub Copilot customization files in VS Code: custom instructions (.instructions.md), prompt files (.prompt.md), custom agents (.agent.md), agent skills (SKILL.md), hooks (JSON), and agent plugins. Use this skill whenever the user asks about customizing Copilot behavior, creating reusable AI workflows, writing copilot-instructions.md, building custom chat agents, automating Copilot tasks with prompt files, or setting up agent skills and hooks in VS Code. Also trigger when the user asks which Copilot customization type to use for a given scenario — always start with the decision matrix below.
Instrument an existing codebase with LaunchDarkly AI Config tracking. Walks the four-tier ladder (managed runner → provider package → custom extractor + trackMetricsOf → raw manual) and picks the lowest-ceremony option that still captures duration, tokens, and success/error.