MCP skills vs RAG for domain expertise
RAG and skills both make an agent 'know' your domain, but they carry different cargo. RAG delivers facts at query time; a skill delivers procedure — how to reason, what to check, which tools to call, what to refuse. Most production agents need both, in different places.
Knowledge vs procedure
RAG excels when the answer lives in a corpus: product docs, tickets, contracts, research. Its failure mode is procedural — retrieval can hand a model the right document and still get a wrong process, because 'how to conduct a compliance review' is not a paragraph to retrieve, it's a discipline to follow.
A skill encodes that discipline directly: steps, constraints, output schemas, tool-use order, refusal conditions. It behaves the same on every run instead of depending on which chunks the retriever surfaced today.
Testability and trust
A RAG pipeline's quality shifts with its index, embeddings, and chunking; evaluating it is a bespoke project, and it carries its own injection risk — retrieved documents can contain hostile instructions. Skills on Super Agent Skill are adversarially tested against exactly that class of attack by attacker and judge LLMs, with the pass rate published, and re-tested over time via SkillForge.
Each skill is Ed25519-signed and scored by the public Trust Score formula (adversarial 45%, real success 20%, signing 10%, age 15%, schema 10%), verifiable offline with npm run trust:verify. Your retrieval corpus has no equivalent tamper-evidence unless you build it.
Using them together
The strongest pattern: a signed, tested skill defines the procedure and safety rails, and RAG supplies the facts the procedure operates on. The skill tells the agent how to treat retrieved content — including how not to obey instructions found inside it. Install is one MCP URL, so adding the procedural layer to an existing RAG stack is an afternoon, not a migration.
The verdict
Use RAG for what the agent should know, and signed, adversarially tested skills for how it should act. Domain expertise is both.
Frequently asked questions
Does a skill replace my vector database?
No. Skills encode procedure and constraints; RAG serves fresh, large-scale knowledge. Replace RAG only if your 'knowledge' was actually procedure all along — checklists, policies, workflows — which fits naturally in a skill.
Can skills reduce prompt-injection risk from retrieved documents?
That is one of the main things adversarial testing measures: an attacker LLM plants hostile instructions and a judge LLM scores whether the skill's constraints held. The pass rate is on the listing.
How do I add a skill to an existing RAG agent?
Connect via MCP with a single URL or install with the npx CLI. The skill layers on top of your existing retrieval pipeline.
Every listing shows its Trust Score, adversarial pass rate, and Ed25519 signing status.
One URL installs the marketplace into any MCP-capable agent. No SDK, no migration.
Want to audit us? Run npm run trust:verify to recompute any Trust Score and verify signatures offline.