Skill UI

Build comprehensive 3-5 year financial models essential for startup planning and fundraising. This skill meticulously projects revenue using cohort-based methods, details cost structures (COGS, S&M, R&D, G&A), plans headcount, and performs detailed cash flow analysis. It calculates critical metrics like LTV, CAC, and burn rate, providing three scenarios (conservative, base, optimistic) for robust strategic decision-making.

This guide provides a comprehensive framework for early-stage companies to track, calculate, and optimize their key performance indicators (KPIs). It covers best practices for various startup business models, guiding teams from the initial seed stage through to Series A funding. Use this skill when developing, analyzing, or refining a structured startup metrics strategy.

Use this resource to implement comprehensive end-to-end monitoring and observability for Supabase projects. It guides users through analyzing API metrics, diagnosing slow database queries using pg_stat_statements, managing log drains for external aggregation, and setting up custom alerts, ensuring optimal project health and performance.

TensorBoard delivers a unified interface to track training metrics, debug network behavior, compare experiments, inspect model graphs, and profile performance for PyTorch or TensorFlow workflows.

This comprehensive skill provides advanced architectural patterns for implementing robust API throttling and rate limiting policies. It covers critical concepts like concurrency limiting, priority queuing, circuit breakers, and adaptive throttling that adjust limits based on real-time backend health metrics (p95/p99 latency). Use this when designing resilient, scalable backend services that must protect themselves from overload and maintain stability under high load.

Automate Token Metrics operations through Composio’s toolkit by orchestrating Rube MCP searches, connection checks, and schema-compliant executions so every `RUBE_MULTI_EXECUTE_TOOL` call runs with up-to-date tooling details and pagination awareness.

A comprehensive tool for tracking and analyzing cryptocurrency derivatives markets. It aggregates key metrics such as funding rates, open interest, liquidations, and options flow across major CEX and DEX exchanges. Use it to identify arbitrage opportunities, gauge market sentiment, predict trend strength, and perform deep risk analysis on perpetual swaps and futures contracts.

A comprehensive foundation skill for monitoring cryptocurrency markets. It provides real-time quotes, 24-hour change metrics, and deep historical price data for over 10,000 coins. Users can track specific symbols, view predefined watchlists (e.g., DeFi, Top 10), or export detailed OHLCV data in CSV format. This skill serves as the foundational data layer for crypto portfolio management, tax calculation, and DeFi analysis applications.

Defines and monitors SLAs, SLIs, and SLOs so teams can set performance targets, track metrics like error budgets and availability, and react before issues impact customers.

Automates the end-to-end training of machine learning models by analyzing datasets, selecting suitable algorithms, tuning parameters, performing cross-validated training, and emitting performance metrics plus a saved model artifact.

Guides Claude to automatically tune machine learning model hyperparameters via grid, random, or Bayesian search, generating runnable Python code, executing validations, and reporting best configurations plus performance metrics for accuracy or other goals.

Provides comprehensive observability for the TwinMind AI meeting system. This skill allows users to monitor critical performance metrics, including transcription quality (using Ear-3 model), meeting coverage, action item extraction accuracy, and memory vault health. It is essential for implementing robust, enterprise-grade AI workflows and managing the operational status of advanced meeting AI applications.