Skill UI

This guide details how to integrate Static Application Security Testing (SAST) tools like CodeQL and Semgrep into your CI/CD pipelines using GitHub Actions. It covers setting up automated vulnerability detection on pull requests, tuning rules to minimize false positives, uploading SARIF results for centralized security reporting, and enforcing quality gates to prevent vulnerable code from merging into protected branches. Essential for DevSecOps and compliance (SOC 2, PCI DSS).

Provides end-to-end guidance for fine-tuning and serving Physical Intelligence’s OpenPI pi0 family (pi0, pi0-fast, pi0.5) with both JAX and PyTorch backends, covering dataset prep, norm stats, checkpoint conversion, and low-latency WebSocket policy inference for ALOHA, DROID, and LIBERO tasks.

A comprehensive guide for optimizing Golang applications, covering systematic approaches to identifying and resolving bottlenecks. It details best practices for reducing memory allocations, improving CPU efficiency, tuning GC, and managing concurrency. The methodology emphasizes profiling first (using pprof, fgprof) and following an iterative cycle: Benchmark → Diagnose → Improve → Benchmark.

Showcases Django project layout, ORM/query tuning, DRF serializer validation, signal usage, middleware timing and anti-patterns to keep apps maintainable and performant.

Produces production-ready Dataverse SDK code for Python, showcasing advanced error handling and retries, batch operations, OData query tuning, metadata lifecycle management, configuration/timeouts, cache invalidation, chunked file uploads, and Pandas integrations with references.

Guides network operators through creating, tuning, and validating RFC 8805-compliant CSV geofeeds with opinionated best practices that improve accuracy, completeness, and usability for publicly routable IP space.

Assistant for PostgreSQL developers that highlights native features, advanced data types, performance tuning patterns, and extension usage to optimize queries, indexes, and analytics in PostgreSQL projects.

Cross-database SQL performance optimization assistant offering query tuning, indexing strategies, pagination, batch operations, and monitoring guidance for MySQL, PostgreSQL, SQL Server, Oracle, and other relational systems.

A comprehensive guide and toolkit for optimizing and monitoring consumption-based costs across the Adobe Creative Cloud ecosystem. It provides strategies and code snippets for tracking usage (credits, transactions) for Firefly, PDF Services, Photoshop, and Lightroom APIs. Use this when implementing usage monitoring, managing billing alerts, or reducing operational expenses related to Adobe API calls.

A comprehensive guide for developers to optimize performance when integrating Adobe APIs (Firefly, PDF, Photoshop). Techniques covered include implementing token caching, parallelizing asynchronous job submissions, leveraging response caching (LRU), and optimizing connection handling to minimize latency and maximize throughput.

This comprehensive guide details advanced strategies for optimizing performance when interacting with blockchain data using the Alchemy SDK. Techniques covered include implementing TTL-based caching for data freshness, achieving parallel multi-chain fetches, utilizing batch API calls (e.g., NFT metadata) to reduce Compute Unit (CU) costs, and adopting WebSockets for real-time event subscriptions. Essential for scaling robust, low-latency dApps.

This skill provides actionable strategies and code patterns to significantly reduce Anima API costs. It focuses on optimizing usage through generation caching, detecting component changes for incremental generation, and implementing smart policies to minimize unnecessary API calls. Ideal for managing large-scale design-to-code workflows and controlling API budget.