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.

analyzing-research-documents

Systematically extract insights, decisions, and constraints from research documents, technical papers, and architectural design files.

markdown-token-optimizer

Analyzes markdown files to identify token-wasting patterns, providing actionable suggestions to optimize documentation for LLM consumption and token efficiency.

developer-growth-analysis

Analyzes Claude Code chat history to identify coding patterns and skill gaps, curates personalized learning resources from HackerNews, and sends progress reports to Slack.

claude-copilot

Analyze markdown documentation files to ensure compliance with predefined AI token budgets and optimize content for efficient AI ingestion.

orchestrator

Autonomous multi-agent orchestration framework for Claude Code with memory-driven workflows, parallel-first task execution, Aristotle-based deconstruction, and multi-stage quality gates.

skill-memory

A Git-backed memory store for agent skills. Download, version, edit, and share custom agent behaviors and procedural knowledge using a CLI.

performance-analysis

Systematic performance engineering: baseline measurement, profiling, bottleneck diagnosis, and evidence-based optimization guidance for high-performance applications.

context-degradation

Diagnose, isolate, and mitigate LLM context failures like lost-in-middle, poisoning, distraction, and context clash to improve agent reliability.

security-hardening

Comprehensive security audit and hardening for AI agents: credential scanning, PII protection, prompt injection defense, and workspace config optimization.

code-search-selector

Intelligent tool selector for code search. Routes queries between semantic (claudemem) and native tools (Grep/Glob) to optimize efficiency, token usage, and search accuracy.

ReasoningBank Intelligence

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