ai

Index AI/LLM capabilities across agents, RAG, and security for discovery and governance.

5|1|Updated Apr 8, 2026

Search Tags:#security #ai #llm #rag #agent #prompt

Ready to run

npx skills add https://github.com/Catsofsuffering/CCGS --skill ai-catsofsuffering

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: ai
Source: https://github.com/Catsofsuffering/CCGS/tree/main/templates/skills/domains/ai
Command: npx skills add https://github.com/Catsofsuffering/CCGS --skill ai-catsofsuffering

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

AI/LLM 能力中枢聚合并路由机构内对 AI/LLM 的能力。它为 Agent 开发、LLM 安全、RAG 系统等能力提供集中视图与规范，帮助团队在面对 AI、LLM、Agent、RAG、Prompt 相关请求时快速定位并应用合适的能力模块。

Core Features & Use Cases

集中索引与路由：对 Agent 开发、LLM 安全、RAG 系统等能力进行结构化梳理，便于跨团队协作与能力落地。
规范化描述：提供统一的能力描述、边界与最佳实践，降低重复工作。
用例驱动：将实际场景映射到可复用模块与工作流，支持快速组装与评估。
使用场景示例：企业在设计 AI 产品时，按需组合 Agent 编排、安全策略与检索系统。
Prompt 工程与评估导航：链接提示设计和评估方法，帮助提升对话与任务执行质量。

Quick Start

Browse the AI capability index to locate the relevant module and begin integrating it into your Codex/OpenSpec workflow.

Frequently Asked Questions about ai

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I index AI and LLM capabilities for agent orchestration?▼

You can index AI and LLM capabilities by structuring agent orchestration, prompt safety, and retrieval systems into a centralized registry. This simplifies discovery and governance by mapping capabilities to standardized workflows with defined guardrails and evaluation criteria.

What is the best way to govern LLM security and prompt safety across teams?▼

Governing LLM security requires applying unified capability descriptions and best practices across a centralized registry. By indexing prompt safety protocols and evaluation criteria, organizations enforce consistent guardrails and reduce duplicated security efforts across cross-team AI development.

Can I use this capability index with OpenSpec workflows and Codex execution gates?▼

Yes, the capability index explicitly maps AI and LLM modules to OpenSpec-driven workflows and Codex/Claude execution gates. This integration ensures selected agent and RAG capabilities align with established execution guardrails and evaluation criteria during product development.

How do I map use cases to RAG and agent modules for AI product design?▼

Mapping use cases requires linking specific scenarios to reusable modules within the capability index. Teams can rapidly assemble RAG systems and agent orchestration workflows by evaluating available indexed components against specific AI product design requirements and evaluation criteria.

Does organizing agent and RAG systems into a central registry reduce duplicate work?▼

Yes, organizing agent and RAG systems into a central registry provides normalized descriptions and boundaries for each capability. This standardization prevents duplicate development efforts by allowing teams to discover and apply existing modules before building new ones.