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Found 42 Skills
Configure OpenAI as embedding provider for GrepAI. Use this skill for high-quality cloud embeddings.
Create and manage agent graphs — directed graphs of AI Configs connected by edges with handoff logic. Use when building multi-agent workflows where configs route to each other.
Migrate an application with hardcoded LLM prompts to a full LaunchDarkly AgentControl implementation in five stages: audit the code, wrap the call, move the tools, add tracking, attach evaluators. Use when the user wants to externalize model/prompt configuration, move from direct provider calls (OpenAI, Anthropic, Bedrock, Gemini, Strands) to a managed config, or stage a full hardcoded-to-LaunchDarkly migration.
Configure PostgreSQL with pgvector for GrepAI. Use this skill for team environments and large codebases.
Create and manage prompt snippets — reusable text blocks referenced inside AI Config variation prompts. Keeps common instructions, personas, and guardrails consistent across multiple configs.
Update, archive, and delete LaunchDarkly AI Configs and their variations. Use when you need to modify config properties, change model parameters, update instructions or messages, archive unused configs, or permanently remove them.
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.
Audit harness configs, discover gaps, usage signals, apply approved fixes. Use when tuning Claude, Codex, Copilot, Cursor, Gemini, Grok, OpenCode, Cherry, or LM Studio. NOT agents, MCP, or app telemetry.
Configure ignore patterns in GrepAI. Use this skill when excluding files and directories from indexing.
Create and configure configs in LaunchDarkly. Helps you choose between agent vs completion mode, create the config, add variations with models and prompts, and verify the setup.
Sync user-level AI configs (~/.claude/, ~/.codex/) with the dotfiles/ directory. Use when dotfiles drift, after sessions that change permissions/hooks, on new machines, or when the user says "sync", "pull dotfiles", "push configs".
Configure AI Config targeting rules to control which variations serve to different users. Enable percentage rollouts, attribute-based rules, segment targeting, and guarded rollouts.