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Found 42 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.
Configure code chunking in GrepAI. Use this skill to optimize how code is split for embedding.
Configure search result boosting in GrepAI. Use this skill to prioritize certain paths and penalize others.
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.
Sets up or repairs the AGENTS.md source-of-truth pattern for any project. Creates a well-structured AGENTS.md with real stack info auto-detected from the project, then wires all AI config satellites (.claude/CLAUDE.md, .github/copilot-instructions.md, .agents/rules/, MEMORY.md) to point to it. Eliminates duplication. Always runs in plan mode — asks before acting. Use this skill whenever the user mentions AGENTS.md, agent config, source of truth for AI rules, setting up Claude/Copilot/Cursor for a project, fixing duplicate AI instructions, or wants to consolidate AI configuration files. Trigger even if the user just says "set up agents" or "fix my AI config".
Create and manage agent graphs — directed graphs of configs connected by edges with handoff logic. Use when building multi-agent workflows where configs route to each other.
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.
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.
Attach judges to AI Config variations for automatic LLM-as-a-judge evaluation. Create custom judges, configure sampling rates, and monitor quality scores.