Skill UI

This guide provides a comprehensive local development setup for LLM applications using Langfuse. It enables fast iteration cycles, real-time trace debugging, and hot reloading, making it ideal for developers building and testing complex AI workflows locally. Instructions cover environment setup, advanced SDK usage, and optional self-hosted Docker deployment.

Guides deliberate skill development during AI-assisted coding by offering optional 10–15 minute exercises after architecture work, schema changes, or “why” questions so developers stay engaged and understand decisions.

Automate Linear project, issue, cycle, label, and comment workflows via the Composio Linear toolkit exposed through Rube MCP, including prerequisite connection checks and optional custom GraphQL queries for advanced cases.

Provides a deep dive into migrating issue tracking data from major platforms like Jira, Asana, and GitHub to Linear. This guide covers the entire lifecycle, including initial workflow assessment, status and priority mapping, data export utilizing API examples, and detailed transformation logic required to ensure data integrity and smooth adoption within Linear.

This comprehensive skill guides the entire product marketing lifecycle, from defining Ideal Customer Profiles (ICP) and developing core positioning statements (e.g., Dunford's method) to executing Go-To-Market (GTM) strategies and product launch plans. It also covers competitive intelligence, building detailed battlecards, and improving sales enablement through win/loss analysis, ensuring successful market entry and adoption across international markets.

This guide provides a comprehensive, production-grade architecture for implementing analytics using PostHog. It covers best practices for event taxonomy design, SDK layering (client and server), feature flag management, and integrating the data pipeline (CDP). Ideal for tracking user lifecycle, feature adoption, and revenue in complex web applications.

This skill demonstrates the multi-model pattern for creating robust and clean API contracts using Pydantic. It guides the creation of separate models for creation requests (Create), updates (Update), responses (Response), and database documents (InDB), ensuring type safety and clear data validation for Python backends. It also covers best practices like handling camelCase aliases and optional fields.

Deploy applications to Render by analyzing repositories, generating render.yaml blueprints, and creating services via MCP tools; works for Git-backed projects and guides users through Render-specific flows, credentials, and Docker image options.

This skill acts as an expert risk manager, providing comprehensive guidance on monitoring portfolio risk, calculating R-multiples, and optimizing position limits. It covers advanced quantitative finance topics such as Value at Risk (VaR), correlation analysis, and stress testing using Monte Carlo simulations. Use it for systematic risk assessment, developing hedging strategies (options/futures), and implementing rigorous risk controls in trading workflows.

Automates environment prep, service orchestration, and cleanup for executing integration test suites, covering database setup, migrations, and optional coverage reports.

Detects real-time significant price movements and unusual volume spikes across cryptocurrency markets. It calculates a composite significance score by combining price change, volume ratio, and market cap. Use it to track top gainers, biggest losers, or identify sudden market pumps across thousands of assets, with filtering options for category and timeframe.

Integrate Sentry into your CI/CD pipeline to achieve end-to-end release tracking. This skill guides you through using the Sentry CLI and SDK to record deployments, associate commits, upload source maps, and monitor crucial release health metrics. Key functions include detecting regressions, calculating crash-free session rates, and tracking user adoption curves for every deployed version.