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Advanced LLM and AI Agent Development

sickn33/antigravity-awesome-skills

Expertise in building production-grade LLM applications, advanced Retrieval-Augmented Generation (RAG) systems, and complex intelligent agents. This skill covers the entire AI lifecycle, including model orchestration, vector search optimization, multimodal integration (vision/audio), MLOps deployment, and robust safety governance for enterprise-level AI solutions.

Advanced LLM and AI Agent Development

sickn33/antigravity-awesome-skills

Expertise in building production-grade LLM applications, advanced Retrieval-Augmented Generation (RAG) systems, and complex intelligent agents. This skill covers the entire AI lifecycle, including model orchestration, vector search optimization, multimodal integration (vision/audio), MLOps deployment, and robust safety governance for enterprise-level AI solutions.

Mastering Job Queues With BullMQ

bullmq-specialist

sickn33/antigravity-awesome-skills

A comprehensive guide to implementing reliable, scalable, and resilient background job processing in Node.js/TypeScript using BullMQ and Redis. Covers advanced patterns such as delayed jobs, repeatable scheduling, job dependencies (flows), rate limiting, robust error handling, and graceful worker shutdown, ensuring production-grade async execution.

Scaling High-Volume Data Processing Pipelines

clay-load-scale

jeremylongshore/claude-code-plugins-plus-skills

A comprehensive guide and code implementation for scaling data enrichment pipelines to handle high volumes (10K-100K+ leads monthly). It covers capacity planning, optimizing batch processing using queues (e.g., BullMQ/Redis), managing rate limits, and designing multi-table architectures for robust, large-scale data ingestion.

LLM Coding Guidelines

coding-guidelines

tech-leads-club/agent-skills

Behavioral rules for LLMs writing or reviewing code, emphasizing caution, simplicity, surgical edits, and goal-driven execution to avoid common mistakes during implementation tasks, bug fixes, or refactors.

Cost-Aware LLM Pipeline Optimization

cost-aware-llm-pipeline

affaan-m/everything-claude-code

A comprehensive pattern for building robust and cost-efficient LLM application pipelines. This guide details combining model routing based on task complexity, immutable cost tracking, limited retry logic, and prompt caching to manage API expenditures while maintaining high quality. Essential for production systems handling variable-complexity, high-volume tasks.

Codebase Structural Memory Protocol

data-structure-protocol

sickn33/antigravity-awesome-skills

A protocol that provides LLM agents with persistent structural memory of a codebase. It maps the project as a directed graph, tracking not only dependencies (what imports what) but also the 'reasons' (why it connects). This allows agents to understand context, perform impact analysis, and navigate large repositories without loading the entire source code into the context window.

Deepgram Scalable Transcription Architecture

deepgram-reference-architecture

jeremylongshore/claude-code-plugins-plus-skills

Provides reference architectures for building high-scale, reliable transcription systems using Deepgram. It covers four main patterns: synchronous REST for short files, async queues (BullMQ) for batch processing, WebSocket for real-time streaming, and a hybrid router for mixed workloads. Use this when designing production-grade audio processing pipelines.

Structured Data Extraction, Batch Scraping, and Mapping

firecrawl-core-workflow-b

jeremylongshore/claude-code-plugins-plus-skills

This advanced workflow executes sophisticated web data gathering tasks. It supports three primary functions: LLM-powered structured data extraction using custom JSON schemas or prompts; efficient batch scraping of multiple known URLs; and rapid site mapping to discover all reachable URLs on a domain. Use this when you require reliable, typed data structures rather than raw markdown content.

Firecrawl Migration Deep Dive

firecrawl-migration-deep-dive

jeremylongshore/claude-code-plugins-plus-skills

A comprehensive guide for migrating web scraping pipelines from tools like Puppeteer, Playwright, and Cheerio to Firecrawl. This skill demonstrates how to replace complex, browser-intensive code with simple API calls, handling single-page scraping, structured data extraction using LLMs, and large-scale site crawling, while eliminating the need for manual browser management and anti-bot workarounds.

On-Device LLM Integration for Apple Platforms

foundation-models-on-device

affaan-m/everything-claude-code

This guide details integrating FoundationModels for running Large Language Models (LLMs) directly on the device (iOS 26). It covers advanced patterns including text generation, extracting structured data using @Generable, implementing custom tool calling for domain logic, and streaming responses for real-time UI updates. Key features emphasize strong privacy and offline capability, ensuring no data leaves the device.

Guided Fuzzing Dictionary

fuzzing-dictionary

trailofbits/skills

Fuzzing Dictionary supplies domain-specific tokens to guide fuzzers when targeting parsers, protocols, configs, or file formats so they reach deeper logic; include magic bytes, headers, keywords, and combine generation from LLMs, headers, or binaries before passing via the fuzzer flag.

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