LLM hallucination checklist
Hallucination-risk controls for agents — check the controls you actually have in production, not the ones on the pitch deck.
Where agents invent (and why pitch-deck controls fail)
Agents invent dates, prices, and CRM facts when tools, RAG citations, or HITL are missing. Teams need a control checklist for go-live — not another survey paper. This LLM hallucination checklist is for ops and agent builders verifying production risk controls before write-backs ship.
How to use this checklist (8 controls)
Tick only the controls you actually have in the live agent (not the deck). Your score is a go/no-go agenda for the next engineering and ops review — not a certificate.
What your score means before you ship write-backs
A low score means block CRM or calendar write-backs, add citation and tool gates, or add HITL — don’t “prompt harder” alone. High scores still need live testing; unchecked items belong in the ship checklist, not a slide.
Checklist
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FAQ
What is an LLM / agent hallucination in production workflows?
A hallucination is when the agent states a date, price, CRM field, policy, or other fact that was not retrieved from a tool, document, or system of record — it was invented from model priors. In production that becomes a wrong quote, a bad calendar invite, or a corrupted CRM write-back.
Does RAG alone stop hallucinations?
No. Retrieval helps, but agents still invent when citations are optional, tools are skipped, or the model is allowed to answer from memory. Pair RAG with mandatory citations, tool-use for live facts, schema validation, and HITL on first runs.
When should the agent say “I don’t know” vs call a tool?
If a fact lives in calendar, CRM, pricing, or a knowledge base, call the tool. If the tool returns nothing or confidence is low, say “I don’t know” and escalate — never guess a date, price, visa rule, or medical/legal claim.
How do schema validation and HITL reduce invented write-backs?
Schema validation rejects malformed or out-of-policy JSON before it hits CRM or calendar. HITL on the first ~20 runs of a new workflow catches invented fields humans would spot immediately — then you tighten prompts, tools, and gates.
How does this differ from a generic AI content detector?
Content detectors score prose for “AI-written” style. This checklist is an agent-ops control list: citations, tool-use, refusal behavior, schema gates, and human review before write-backs. It is about production risk, not essay originality.
Need a production agent with these controls built in?
GoWith agentic builds wire citation, tool-use, schema validation, and HITL into workflows your team can run — not a one-off demo chat. See all free tools, the HITL gate picker, and the agent vs workflow scorer for the rest of the agent-quality lane.
Educational only. Not legal advice and not a substitute for testing the live agent. LLM hallucination checklist runs in your browser — nothing is sent to your CRM unless you copy it yourself.
Related agent-quality tools
If more than a few boxes are open, your agent isn’t ready for CRM or calendar write-backs. Start a free trial or book a consult — we’ll wire citation, tool-use, and HITL gates into a production agentic workflow, not a demo chat.