ai-rag-defense
Skill1 starsChanged 6 months agoMITView on GitHub
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.
In this repository21 other files it gives its agents.
- ai-context-engineeringSkill
- ai-context-engine-productionSkill
- ai-context-engineSkill
- ai-dataset-engineeringSkill
- ai-evaluationSkill
- ai-finetuningSkill
- ai-foundation-modelsSkill
- ai-inference-optimizationSkill
- ai-multi-agent-mcpSkill
- ai-production-architectureSkill
- ai-prompt-engineeringSkill
- ai-rag-and-agentsSkill
- ddia-architectureSkill
- ddia-batch-stream-processingSkill
- ddia-data-ethicsSkill
- ddia-data-modelingSkill
- ddia-replication-shardingSkill
- ddia-transactions-consistencySkill
- job-description-analyzerSkill
- resume-content-writerSkill
- resume-fit-scorerSkill
The file
We split this skill into the rules it gives an agent
1 rule. About 0 are common, 0 are distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈0
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 21
Check guidelines.md to find which files to load
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
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.mdto find which files to load - Load only relevant files (each topic has knowledge.md, rules.md, examples.md)
- 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 |
Guidelines
See guidelines.md for task-based file selection.
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