Hallucination Citation Checker
$2.99OfficialUse when auditing an LLM answer that carries source citations, to verify each claim is entailed by its cited sources and flag unsupported or misattributed ones.
datahallucinationcitationsfaithfulnessnliattributionragverification· by SkillingMain
What you get
- ✓9-step procedure
- ✓Runnable Python / JSON included
- ✓7-point quality checklist
- ✓7 pitfalls to avoid
- ✓Installs into 6 tools
- Version
- v1 →
- Last updated
- today
- Length
- 7 min read
- Requires
- Best with a strong model (Claude Opus 5)
Works in: Claude Code, Codex, Cline, opencode, OpenClaw, Hermes · Built for large codebases
Preview
When to use
Invoke to audit an already-written answer that carries source citations and decide, claim by claim, whether each statement is actually backed by what it cites. Trigger on:
- A RAG/research pipeline emits an answer with markers (
[1],(Smith 2021), footnotes) and you must gate it before shipping. - A reviewer flags a "confident but wrong" or "citation looks fabricated" complaint.
- You are grading another model's output for faithfulness / attribution.
- Regulated output (legal, medical, financial) where an unsupported claim is a liability.
Do not use this for open-ended fact-checking with no supplied sources — that is a retrieval task. Here the sources are given; veri
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