Skill UI

Guides diagnosing Buttercup CRS Kubernetes issues across the crs namespace by triaging pod states, analyzing logs, checking resource pressure, monitoring Redis, and inspecting queues for cascading failures in services such as redis, build-bot, scheduler, and UI.

A disciplined debugging ritual that forces you to investigate errors, reproduce issues, and analyze patterns before proposing fixes, ensuring root causes are understood across multi-component systems and minimizing risky guesswork under pressure.

Guides authors through adapting test-driven development to agent skills documentation, covering when to create skills, required background, directory structure, and how to run pressure scenarios to ensure compliance before publishing.

Guides AI agents through analyzing working code, spotting overly complex structures, then refactoring for clarity while preserving exact behavior and project conventions, especially after reviews or high-pressure edits.

A type-safe, generics-first implementation of ReactiveX for Go. It manages complex asynchronous, event-driven pipelines, providing core features like automatic backpressure, comprehensive error propagation, and Go context integration. Use this library when handling infinite streams, real-time data processing, or building advanced event-driven architectures beyond simple channel usage.

This comprehensive guide details advanced techniques for optimizing Bright Data API scraping performance. It covers implementing connection pooling, robust response caching layers (LRU Cache), and managing concurrent requests with backpressure control. Use this when facing slow API responses or requiring high-throughput, scalable data extraction.

This guide provides production-ready patterns for using the @clickhouse/client library in Node.js. It covers critical, real-world scenarios such as safe typed queries, streaming large data inserts (with backpressure handling), robust batch operations with retries, and streaming SELECT queries for low memory consumption. It also includes best practices for comprehensive error handling and connection lifecycle management, ensuring stable and scalable ClickHouse integrations for data pipelines.

This guide provides advanced techniques to optimize integration performance with the MindTickle API. It addresses common enterprise bottlenecks such as slow learner progress queries, rate limit errors, and high-volume webhook backpressure. Techniques covered include implementing Redis caching, using offset-based pagination for bulk data retrieval, managing concurrent requests with connection pooling, and applying exponential backoff for robust rate limit handling.

A throughput-first interrogation tool designed to pressure-test major engineering plans. It rigorously reviews six critical areas—including DORA metrics, cycle time, hiring funnel health, team structure, and production discipline—before committing to delivery milestones, hiring waves, or organizational changes.

This skill performs a comprehensive compliance pressure test against the EU AI Act. It systematically assesses any AI system across six critical dimensions: prohibited practices, high-risk classification, conformity assessment, provider role definition, transparency obligations, and systemic risk, ensuring readiness for EU market deployment.

This skill simulates a Data Protection Officer (DPO) audit, pressure-testing privacy compliance across six critical, Article-cited GDPR areas. It is essential for pre-annual audits, post-breach assessments, DPA investigations, and M&A due diligence, ensuring readiness across RoPA, lawful basis, DPIA, DSAR, and international data transfers.