Skill UI

Skill Security Auditor scans AI agent skills before installation, flagging command injections, prompt tampering, dependency risks, and filesystem abuses while providing verdicts and remediation guidance for CLIP plugins or Codex skills.

Analyzes Claude Code auto-memory, promotes stable learnings to CLAUDE.md/.claude/rules, extracts reusable skills, monitors MEMORY.md health, and provides review/promotion/extraction commands to keep project knowledge curated and actionable.

Coordinates discovery, matching, and workflow orchestration across agent ecosystems, automatically scanning SKILL.md, ranking relevant skills, and executing multi-step plans for complex requests.

Evaluates incoming requests, decides if specialized skills are needed, orchestrates optimal combinations, and logs successful pairings in agent-memory while guarding against overusing complex tools on simple tasks.

Analyzes Claude Code session components to estimate token usage, flag bloated agents/skills/rules/MCP servers, and deliver prioritized savings recommendations plus optional verbose breakdowns before adding new pieces.

Discover, download, and manage reusable AI agent skills from the AionUI Skills registry, making it easy to augment autonomous assistants with community-built capabilities whenever a task benefits from specialized functionality.

Provides command-line recipes for hitting DeerFlow HTTP endpoints to start threads, stream runs, manage memory/models/skills/agents, and upload files for in-depth research tasks.

A comprehensive meta-skill template designed for developers to scaffold, structure, and define specialized Agent Skills for AI platforms like GitHub Copilot. It guides users through mandatory requirements, including folder naming conventions, YAML frontmatter best practices (name, description), and structuring the skill body with detailed workflows and documentation sections. Use this when building complex, specialized AI capabilities.

Acontext serves as a robust memory layer for production-grade AI agents. It provides persistent sessions, disk-based storage, and sophisticated learning spaces that distill complex conversations into reusable, structured skills. Users can manage the entire system—from project setup and login to skill uploading—via a powerful Command Line Interface (CLI) and API, significantly enhancing agents' contextual understanding and long-term knowledge retention.

The ClawHub CLI provides a comprehensive command-line interface for managing agent skills. Users can use it to search for new skills, install specific versions, update existing skills across a project, and publish their own skills back to the ClawHub registry. It is essential for developers building and deploying AI-powered applications in the ClawHub ecosystem.

This tool provides comprehensive AI security scanning using the Tencent AI-Infra-Guard framework. It systematically audits AI infrastructure, scans tools and skills, checks agent security, and performs advanced LLM jailbreak evaluations to identify vulnerabilities and ensure the robustness and reliability of AI systems.

A universal infrastructure for automatically evolving and optimizing AI agents across any domain. Using LLM-driven mutation and iterative solve-observe-evolve cycles, it enhances critical components like prompts, skills, and memory by benchmarking performance against measurable datasets, enabling the creation of self-improving AI systems.