Agent Skills Hub

vercel

Deploy and manage Vercel projects, including linking repositories, environment variables, and domain configurations.

sparc-methodology

SPARC methodology for multi-agent development: systematic Specification, Pseudocode, Architecture, Refinement, and Completion workflows via Claude Flow orchestration.

react

React component development guide for LobeHub, including styling with antd-style, layout building with @lobehub/ui, and routing management.

cursor-diary

Maintains a detailed, step-by-step implementation diary for coding sessions with docmgr integration to track changes, rationale, commands, and failures.

context-management

Proactive context window management for AI agents via intelligent token monitoring, snapshot creation, and selective state rehydration to maintain continuity during long sessions.

arduino-mcp

An MCP server enabling agents to edit, manage, and compile Arduino IDE 2.0 sketches, including source code manipulation and automated build capabilities via arduino-cli.

build-iphone-apps

CLI-only iOS development agent for Swift, SwiftUI, and UIKit. Handles the full lifecycle: build, debug, test, and release without Xcode.

skill-architect

Expert consultant for designing and building high-quality, consistent AI agent skills. Guides you through discovery, architecture, and creation phases to ensure reliable, composable, and efficient skill delivery.

legal-risk-assessment

Assess and classify legal risks using a severity-by-likelihood framework. Evaluate contract risk, deal exposure, and issue severity to determine if senior counsel or external review is required.

regression-testing

Strategic regression testing with intelligent test selection, impact analysis, and continuous regression management for faster, more reliable software delivery.

python-plan-optimization

6-phase read-only Python analysis workflow that identifies design principle violations, code smells, and modernization opportunities based on specific project types (POC to Open Source).

overview

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