GroundCheck

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Single-agent, evidence-grounded claim verification — catch fabricated facts by checking each claim against real evidence, not by asking more models to agree.

GroundCheck takes content that already exists — a generated answer, a report, RAG output, docs, or code — extracts the verifiable claims, grounds each one in real evidence, and returns a per-claim verdict with citations plus an action: keep / revise / retract / send back.

Why single-agent (and why that matters)

Multi-agent debate is good at fixing overconfidence — but it can reinforce a shared hallucination, because several models trained on similar data confirm the same wrong fact. GroundCheck deliberately does not use a panel: it grounds every claim in deterministic external evidence (tests, source, docs, web, retrieved context).

• GroundCheck → treats hallucination (single-agent + evidence grounding)
• agent-arena → treats overconfidence (multi-agent debate)

They form one verification stack at two depths and interoperate via a shared Claim Ledger.

What it produces

For each claim: an atomic, classified, dated verdict — supported · partially_supported · refuted · unverifiable · outdated · needs_qualification — with cited evidence and a recommended action. Compound claims are decomposed so a true sub-claim can't launder a false bundled conclusion.

The ledger is contestable, not authoritative: every verdict is traceable, time-bounded, and can be reopened with stronger counter-evidence. The verifier can be wrong too.

Use as a fact-gate in any multi-agent system

GroundCheck is a generic, pluggable verification gate — agent-arena, CrewAI, AutoGen, LangGraph, or any orchestrator can plug it via the fact-gate contract:

each agent answers independently
   → PRE-DEBATE gate: groundcheck per answer
       → refuted? send back to that agent (with evidence) before debate
   → debate
   → POST-DEBATE gate: re-check new/changed claims

Catching factual errors before debate is what stops a panel from reinforcing a shared hallucination. Send-backs carry evidence, not conclusions, and the original answer stays immutable — so the source agent reasons independently instead of appeasing the checker.

When to use / not use

Use: verify claims · check for hallucinations · "are these citations / numbers / APIs real" · fact-check before publishing · RAG groundedness · as a fact-gate in a multi-agent flow.

Not for: pure opinions / creative content · code logic already covered by tests · "which option is better" decisions (that's agent-arena).

Install

npx skills add zhjai/groundcheck -g -a claude-code

Works with Claude Code, Codex, Cursor, OpenCode, and other Agent Skills hosts. Or copy skills/groundcheck/ into your agent's skills directory.

Status

v0.1.0 preview. Not affiliated with any vendor. MIT licensed.