grounding-verification

Compare scrubbed versus full evidence to detect potential confabulation.

Updated Aug 27, 2026
One-click install
npx skills add https://github.com/gitwalter/cursor-agent-factory --skill grounding-verification
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: grounding-verification
Source: https://github.com/gitwalter/cursor-agent-factory/tree/main/.cursor/skills/grounding-verification
Command: npx skills add https://github.com/gitwalter/cursor-agent-factory --skill grounding-verification

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Universal two-pass grounding verification helps detect when an LLM's claims are unreliable by comparing a scrubbed, anonymized evidence pass with a full, detailed pass.

Core Features & Use Cases

  • Two-pass verification workflow: scrubbed vs full evidence, delta calculation, and a clear verdict (VERIFIED, PLAUSIBLE, SUSPICIOUS, or UNSUPPORTED).
  • Profile-driven thresholds for domains like code, documentation, data schemas, and security.
  • Deterministic, structured output suitable for integration and auditing.
  • Use Case: Validate software documentation claims against API schemas to guard against hallucinated documentation.

Quick Start

Prepare two passes of evidence (scrubbed/anonymized and full) for your LLM's claims, run the verification, and inspect the VERIFICATION REPORT for verdicts and Delta scores.

Frequently Asked Questions about grounding-verification

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I detect LLM hallucinations in generated documentation?

LLM hallucination detection compares scrubbed versus full evidence passes to flag confabulation. This grounding verification calculates a delta between the two passes to output a clear verdict, such as VERIFIED or UNSUPPORTED, for your claims.

What is two-pass grounding verification for LLM outputs?

Two-pass grounding verification is a deterministic method comparing an anonymized evidence pass against a full detailed pass. It calculates a delta score to determine if LLM claims are reliable and outputs a structured, auditable verdict.

How do I audit LLM claims against API schemas?

You audit LLM claims against API schemas by running them through a profile-driven verification process. Using domain-specific thresholds for code or data schemas, the process outputs a structured report indicating whether the claims are VERIFIED or SUSPICIOUS.

Does grounding verification work for both code and security domains?

Yes, grounding verification works across domains like code, documentation, data schemas, and security. It applies profile-based thresholds tailored to each specific domain to evaluate the reliability of LLM claims.

What do I need to provide to run a grounding verification check?

To run a grounding verification check, you need to provide frontmatter with a name and a verification profile. You must also prepare two passes of evidence, one scrubbed and one full, to compare against your LLM claims.