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Found 58 Skills
Onboard a project to LaunchDarkly: kickoff roadmap, resumable log, explore repo, MCP, companion flag skills, nested SDK install (detect/plan/apply), first flag. Use when adding LaunchDarkly, setting up or integrating feature flags in a project, SDK integration, or 'onboard me'.
Create, list, remove, and run scheduled autonomous Claude Code agents. Agents run on a timer via macOS launchd, execute any prompt headlessly, and deliver results via Beeper messages and macOS notifications. Use for recurring research, monitoring, overnight builds, or any task you want Claude to do on autopilot.
Set up and run experiments in LaunchDarkly. Create experiments with metrics and treatments, start iterations to collect data, and monitor results.
Control LaunchDarkly feature flag targeting including toggling flags on/off, percentage rollouts, targeting rules, individual targets, and copying flag configurations between environments. Use when the user wants to change who sees a flag, roll out to a percentage, add targeting rules, or promote config between environments.
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.
Apply LaunchDarkly SDK onboarding: install dependency (or dual-SDK pair), configure env and secrets with consent, add init at entrypoint(s), verify compile. Nested under sdk-install; next is run.
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.
Detect repository stack for LaunchDarkly SDK onboarding: languages, frameworks, package managers, monorepo targets, entrypoints, existing LD usage. Nested under sdk-install; next is plan.
Configure the LaunchDarkly hosted MCP server during onboarding. Use when the parent LaunchDarkly onboarding skill reaches Step 4 (MCP). Supports Cursor, Claude Code, Windsurf, GitHub Copilot, and other MCP-compatible agents. OAuth authentication; no API keys for the hosted server.
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.
Enables agents to register, manage, and execute scheduled tasks using OS native scheduler (crontab for Linux/WSL, launchd for macOS). No git, no dangerous flags, no session dependency. Tasks run headless, output to log files, user reads when ready. Use this skill when: - User wants to schedule recurring tasks with natural language - User mentions "every day at", "cada hora", "schedule", "programar", "automatizar" - User needs tasks to run without open session (headless) - User wants OS-level scheduling (crontab/launchd) - User mentions "cada minuto durante la próxima hora" or temporal intervals ACTIVATE when user mentions: "schedule", "programar", "cron", "cada día", "every hour", "automate", "tarea programada", "ejecutar automáticamente", "recordatorio", "cada minuto durante", "durante la próxima", "intervalo", "task scheduler", "opencode headless", "kiro scheduled", "background task", "tarea en segundo plano" DO NOT USE for: git operations, dangerous permissions, MCP sampling dependency.
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.