Agent Skills Hub

cc-stack-analysis

Expert tool for auditing and validating the structural integrity, naming conventions, and best practices of Claude Code configurations, including skills, hooks, and commands.

mermaid-visualizer

Transform text into professional Mermaid diagrams. Automatically handles syntax, subgraphs, and layout rules for clean flowcharts, sequence diagrams, and process maps.

novelty-check

Verify research idea novelty against recent literature. Use when user says '查新', 'novelty check', or needs to confirm if a method is original.

security-hardening

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

subagents-orchestration-guide

Orchestrates multi-agent development workflows, managing task decomposition, requirement analysis, and quality assurance for complex software projects.

overview

Foundational mental model and operational rules for using TraceMem to ensure secure, auditable, and compliant AI agent execution.

context-bar

A color-coded, real-time context usage progress bar for the Claude Code statusline and manual on-demand checks.

dev-workflow

Full-stack SDLC agent workflow managing the entire production lifecycle from intake and planning to automated testing, CI/CD, and infrastructure deployment using MCP tools.

using-superpowers

The foundational skill for the Superpowers methodology. Ensures agents correctly identify and invoke required development skills before starting any task or conversation.

context-driven-testing

Apply context-driven testing principles to adapt testing strategies based on project goals, risks, and constraints rather than relying on universal best practices.

toh-framework

Security-first auditing framework for AI-generated code. Provides multi-level protection including hardcoded secret detection, dangerous pattern identification, and comprehensive vulnerability audits for modern web applications.

scientific-critical-thinking

Evaluate scientific claims and research methodology for rigor, bias, and validity. Use evidence-based frameworks like GRADE and Cochrane to analyze experiments, protocols, and study conclusions.