Agent Skills Hub

context-engineering-expert

Advanced context engineering system for orchestrating AI agents, memory management, and token optimization to improve long-term persistence and project intelligence.

data-engineer

Specialized data engineering agent for designing ETL/ELT pipelines, defining data schemas, managing data quality, and implementing robust ingestion workflows.

codeql

Perform deep security analysis on codebases using CodeQL for interprocedural data flow, taint tracking, and automated vulnerability detection across multiple languages.

rclone

Manage, sync, and transfer files between local storage and cloud providers like S3, Cloudflare R2, Backblaze B2, Google Drive, and Dropbox using rclone.

meeting-insights-analyzer

Analyze meeting transcripts to uncover behavioral patterns, communication insights, and leadership feedback. Identify conflict avoidance, filler words, speaking ratios, and active listening to improve your professional presence.

qmd

Local hybrid search engine for markdown notes, documentation, and codebase knowledge bases to reduce token consumption and improve retrieval efficiency.

auto-trading-strategy

Professional trading strategy and risk management toolkit for prediction markets and crypto, featuring trend analysis, position sizing, and stop-loss frameworks.

web-search

Autonomous research specialist for verified information gathering, source evaluation, and structured synthesis.

literature-engineer

Evidence-first literature collector for automated research pipelines. Scales paper pools to 1200+ with metadata normalization, provenance tracking, and multi-source ingestion.

ReasoningBank Intelligence

Implement adaptive learning with ReasoningBank for pattern recognition, strategy optimization, and continuous improvement in AI agents.

projection-patterns

Build read models and projections from event streams for CQRS, materialized views, and optimized query performance in event-sourced systems.

basic-usage

Essential guide to llmemory for document storage and search: installation, database setup with pgvector, document ingestion, hybrid/semantic retrieval, and building RAG systems with multi-tenant support.