How do I install the AI RAG Defense skill?

Run npx skillmds@latest add ebarti/ai-rag-defense in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is AI RAG Defense safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with AI RAG Defense?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is AI RAG Defense free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published AI RAG Defense?

ebarti (@ebarti) published this skill. Their other Agent Skills are listed on their SkillMD profile.

AI RAG Defense by ebarti — Agent Skill

Name: AI RAG Defense
Author: ebarti

AI RAG Defense

Token reduction, retrieval fidelity, and prompt-injection defense layers for the Context Engine. Covers a Summarizer agent for proactive context reduction, micro-context engineering (prompt design inside agents), high-fidelity RAG with source-metadata citations, layered untrusted-context defenses against prompt injection, and grounded-reasoning validation that prevents hallucination. Use this skill when: - Reducing token costs by adding a Summarizer agent - Designing system prompts inside specialist agents (micro-context) - Adding citations and source metadata to RAG outputs - Defending agents against prompt injection / data poisoning - Validating agent reliability across high-fidelity / summarization / grounded test cases - Preventing hallucination when retrieval returns no result

ebarti a07a6c4 25 files · 138.5 KB Updated Sep 17, 2026

File contents

AI RAG Defense

Knowledge from "Context Engineering for Multi-Agent Systems" (Chapters 6-7). The reduction, fidelity, and defense layers that turn a working engine into a trustworthy one.

Quick Start

Check guidelines.md to find which files to load
Load only relevant files (each topic has knowledge.md, rules.md, examples.md)
Apply guidance to your work

References

Category	Purpose
`summarizer-agent`	Cost-management agent for proactive context reduction
`micro-context-engineering`	Prompt design inside agents (macro vs micro)
`high-fidelity-rag`	Source-metadata-on-chunks pattern, citations-mandatory Researcher
`input-sanitization`	Untrusted context boundary, prompt-injection threat model + smells
`grounded-reasoning`	Report-negative-finding pattern, multi-case validation

Workflows

Workflow	Purpose
`workflows/add-summarizer.md`	Integrate Summarizer agent for proactive context reduction
`workflows/add-citations.md`	Upgrade RAG to high-fidelity (source metadata + cite)
`workflows/defend-against-injection.md`	Add untrusted-context boundary + run grounded-reasoning validation suite

Guidelines

See guidelines.md for task-based file selection.

---name: ai-rag-defensedescription: Token reduction, retrieval fidelity, and prompt-injection defense layers for the Context Engine. Covers a Summarizer agent for proactive context reduction, micro-context engineering (prompt design inside agents), high-fidelity RAG with source-metadata citations, layered untrusted-context defenses against prompt injection, and grounded-reasoning validation that prevents hallucination. Use this skill when: - Reducing token costs by adding a Summarizer agent - Designing system prompts inside specialist agents (micro-context) - Adding citations and source metadata to RAG outputs - Defending agents against prompt injection / data poisoning - Validating agent reliability across high-fidelity / summarization / grounded test cases - Preventing hallucination when retrieval returns no result---# AI RAG DefenseKnowledge from "Context Engineering for Multi-Agent Systems" (Chapters 6-7). The reduction, fidelity, and defense layers that turn a working engine into a trustworthy one.## Quick Start1. Check `guidelines.md` to find which files to load2. Load only relevant files (each topic has knowledge.md, rules.md, examples.md)3. Apply guidance to your work## Contents### References| Category | Purpose ||----------|---------|| `summarizer-agent` | Cost-management agent for proactive context reduction || `micro-context-engineering` | Prompt design inside agents (macro vs micro) || `high-fidelity-rag` | Source-metadata-on-chunks pattern, citations-mandatory Researcher || `input-sanitization` | Untrusted context boundary, prompt-injection threat model + smells || `grounded-reasoning` | Report-negative-finding pattern, multi-case validation |### Workflows| Workflow | Purpose ||----------|---------|| `workflows/add-summarizer.md` | Integrate Summarizer agent for proactive context reduction || `workflows/add-citations.md` | Upgrade RAG to high-fidelity (source metadata + cite) || `workflows/defend-against-injection.md` | Add untrusted-context boundary + run grounded-reasoning validation suite |## GuidelinesSee `guidelines.md` for task-based file selection.

Frequently asked questions

AI RAG Defense

File contents

AI RAG Defense

Quick Start

Contents

References

Workflows

Guidelines

Related skills

Frequently asked questions

How do I install the AI RAG Defense skill?

What does the AI RAG Defense skill do?

Is AI RAG Defense safe to use?

Which AI agents work with AI RAG Defense?

Is AI RAG Defense free to use?

Who published AI RAG Defense?