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Found 3,523 Skills
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.
Use when creating a new Zeabur project. Use when deploying templates to a new project. Use when user says "create project", "new project", or "set up a new environment".
The fastest and easiest way to build with Stream: Chat, Video, Feeds and Moderation — including live SDK docs search.
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.
Appwrite Rust SDK skill. Use when building server-side Rust applications with Appwrite. Covers async client setup with API keys, user management, TablesDB database/table/row operations, file storage, function executions, permissions, queries, and error handling. Uses the crates.io `appwrite` package and Tokio.
Searches the live web via Nimble APIs to monitor competitors and produce a structured intelligence briefing. Runs parallel searches for news, product launches, hiring signals, and funding — then compares against previous findings to highlight only what's new. Use this skill when the user asks about competitors, competitive intelligence, or what rival companies are doing. Common triggers: "what are my competitors doing", "competitor update", "competitor news", "competitive landscape", "market intel", "what's new with [company]", "track [company]", "competitor briefing", "who's making moves", "competitive analysis", "losing deals to [company]", "battlecard". Also use before board meetings or strategy sessions when the user wants competitive context. Requires the Nimble CLI (nimble search, nimble extract) for live web data. Do NOT use for single-company deep dives (use company-deep-dive), meeting prep with attendees (use meeting-prep), or non-business queries.
Set up and run experiments in LaunchDarkly. Create experiments with metrics and treatments, start iterations to collect data, and monitor results.
Roll out self-serve analytics on MotherDuck for internal teams. Use when deciding the first governed dataset, the first Dive or share, ownership boundaries, and the rollout path from one audience to broader adoption.
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.
Help developers build with Chainlink Data Streams, including credentials guidance, report decoding, REST and WebSocket report retrieval with official Go/Rust/TypeScript SDKs, High Availability streaming, on-chain report verification, real-time frontend displays, report schema guidance, SQLite persistence, and timestamp lookback. Use this skill whenever the user mentions Chainlink Data Streams, Streams Direct, Data Streams reports, report schemas, report decoding, data-streams-sdk, or real-time low-latency market data from Chainlink.
End-to-end interactive workflow — pick a product, then either run existing tasks and environments (Path A) or set up new ones from docs, suggested tasks, credentials, and templates (Path B). Builds the experiment, attaches signals, and optionally triggers the first iteration. Trigger when users say: "set up an experiment", "create an experiment", "I want to run an experiment", "run my tasks", "setup experiment", "new experiment", "configure an experiment", or "experiment setup".
Instruments code so production behavior is visible and diagnosable. Use when adding logging, metrics, tracing, or alerting. Use when shipping any feature that runs in production and you need evidence it works. Use when production issues are reported but you can't tell what happened from the available data.