Skill UI

Provides foundational knowledge and implementation patterns for connecting to the Procore API. This skill details how to securely implement OAuth2 authentication (using the Client Credentials flow) to manage data in critical construction processes, including project tracking, RFIs, and document submittals.

This skill applies a rigorous, evidence-first discipline to coding tasks, inspired by Fable-like best practices. It guides agents through a structured workflow: inspecting the workspace, tracking goals and findings, grounding all conclusions in verifiable evidence, and executing thorough verification gates before declaring completion. Ideal for complex development, debugging, or adapting cross-model prompt guidance into robust, verifiable project rules.

EAS Observe is a comprehensive tool for monitoring performance metrics in production Expo applications. It tracks critical performance data, including app startup time, navigation performance across routes, and custom user events. Developers can integrate it into their Expo project using the `expo-observe` package and query detailed reports via the EAS CLI, ensuring optimal user experience and stability.

Computes USD-per-day burn rate from recent cost-tracking sessions and linearly projects spend to 7d/30d/90d/365d horizons, including days until budget exhaustion.

This tool restores project context, crucial after a session clear. It comprehensively analyzes Git history, summarizing recent commits, tracking uncommitted changes, scanning for outstanding TODOs/FIXMEs, and verifying the current project structure. It helps developers quickly re-establish the full working context to resume work efficiently.

This skill enables Real User Monitoring (RUM) for browser and web applications using the Application Insights JavaScript SDK. It tracks page views, clicks, AJAX dependencies, exceptions, and custom events. Supports React, Angular, and React Native instrumentation. Includes GenAI agent traces with backend correlation. Ideal for frontend performance and error tracking in TypeScript projects.

This skill manages the full lifecycle of major feature development. It includes researching the project, creating a phased implementation plan, tracking progress, and verifying outcomes before completion. Use it to coordinate status, next steps, and phased delivery for feature efforts. It ensures structured workflows across research, planning, implementation, and tracking phases.

This skill applies a rigorous, evidence-first discipline to coding tasks, inspired by Fable-like best practices. It guides agents through a structured workflow: inspecting the workspace, tracking goals and findings, grounding all conclusions in verifiable evidence, and executing thorough verification gates before declaring completion. Ideal for complex development, debugging, or adapting cross-model prompt guidance into robust, verifiable project rules.

Maintain durable feature-level memory across AI coding sessions using lightweight Markdown tracks. It organizes status, source-of-truth docs, decisions, risks, and changes for long-lived features. Helps AI agents resume work accurately without relying on chat history. Ideal for repositories needing structured project memory without reorganizing all documentation.

A comprehensive automation toolkit for managing Sentry error tracking and monitoring operations. Users can programmatically investigate issues, configure project-level alert rules, manage release versions, and monitor organizational structure. Essential for DevOps and development teams needing deep integration and programmatic control over error data.

This skill provides a robust system for tracking all code modifications using structured JSON records and enforcing a defined state machine (e.g., planned -> deployed). It is critical for AI coding workflows, ensuring that if a session expires or is abandoned, the next session receives the full context, progress summary, and blockers to resume seamlessly. Ideal for complex, multi-stage development projects and onboarding new codebases.