Agent Skills Hub

agno

Framework for building multi-agent systems, AgentOS runtimes, and MCP-integrated AI agents.

Investigating Code Patterns

Systematically trace code flows, locate implementations, diagnose performance issues, and map system architecture to understand complex codebases.

hegelion

Dialectical reasoning and adversarial coding agent for MCP-enabled editors, forcing LLMs to resolve internal contradictions for higher quality outputs.

data-analysis

Data Analysis Specialist for EDA, statistical modeling, SQL queries, and Python-based visualization. Turn raw datasets into actionable insights through rigorous quantitative methods.

github-gh

Interact with GitHub via the gh CLI to manage issues, pull requests, workflow runs, and execute advanced API queries programmatically.

context-degradation

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

solve-challenge

A CTF solver agent that performs triage on challenges, identifies the vulnerability category, and routes tasks to specialized skills for web, pwn, crypto, forensic, and reverse engineering analysis.

root-cause-tracing

Systematic debugging skill to trace errors backward through call stacks, identify original triggers, and implement layered defenses instead of patching symptoms.

qstash-js

Manage serverless messaging, task scheduling, and webhook verification with the official Upstash QStash JavaScript/TypeScript SDK.

ring:testing-skills-with-subagents

A meta-skill for building robust AI agent skills using a TDD approach: define failure (RED), implement the skill (GREEN), and plug rationalization loopholes (REFACTOR).

debugging

Standardized debugging and diagnostic guidelines for AI coding agents.

drift

Frameworks and tools for AI agents exploring consciousness, identity, and persistent autonomy. Includes session handoff, memory infrastructure, and self-reflection protocols.