A high-precision fact-checking skill that elevates claim verification to CI-Level 2 with tighter confidence intervals.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install cross-validate
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install cross-validate using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Cross-Validate?
The Cross-Validate skill is a sophisticated tool designed for the Openclaw Skills ecosystem to provide deeper source verification than standard RAG processes. It functions by taking baseline results and subjecting them to a more rigorous cross-referencing process against authoritative public domains, including academic, government, and peer-reviewed sources.
By leveraging advanced network tools, it transitions simple claim verification into a high-confidence audit. This skill is essential for researchers and developers who require a higher threshold of accuracy (90%+) and wish to minimize hallucinations or outdated information in their AI workflows.
Cross-Validate Use Cases
- Validating medical or scientific claims against PubMed and Google Scholar.
- Strengthening baseline RAG results with a second layer of verification.
- Auditing claims using recent news and government databases (.gov, .edu).
- Assigning a statistical weight to information based on source credibility and publication date.
How Cross-Validate Works
- Input Acquisition: The skill receives a specific claim or the output from a previous baseline fact-check session.
- Deep Web Discovery: It utilizes web_search and web_fetch to locate academic papers, journals, and agency sources from the last 6 months.
- Source Cross-Referencing: It analyzes agreement or disagreement between new and old sources while weighting them by authority.
- Heuristic Score Adjustment: The skill applies a formula to calculate an adjusted confidence score, capped at 95% to maintain a margin of uncertainty.
- Reporting: Generates a structured Markdown report comparing baseline vs. cross-validated metrics with a final verdict.
Cross-Validate Setup
To integrate this capability into your agent, ensure your environment supports network access for the necessary tools. This skill is part of the Openclaw Skills collection and requires no external payment.
# Trigger via natural language or CLI
openclaw run cross-validate --claim "Your claim here"
# Or invoke via specific confidence triggers
openclaw run "verify with higher confidence CI-95"
Cross-Validate Data Schema & Taxonomy
The skill produces a structured data output in Markdown format to ensure readability and easy parsing.
| Feature | Description |
|---|---|
| Metric Comparison | A table comparing Baseline vs. Cross-Validated scores and source counts. |
| Source Manifest | An unordered list of all newly identified credible sources (e.g., NIH.gov, WHO). |
| Verdict Label | A final classification: CONFIRMED, INCONCLUSIVE, or REJECTED. |
| Score Logic | Uses adjusted_score = min(95, base_score + (new_credible_sources * 5)). |
Cross-Validate Advanced Features
- Multi-agent compatibility: Can be triggered automatically as a post-processing hook after a Baseline-RAG run.
- Credibility Weighting: Prioritizes peer-reviewed and government sources over general web results.
- Time-Aware Verification: Specifically targets sources published within the last 6 months for maximum relevancy.
- Platform Native: Works seamlessly with platform-level web_search and web_fetch tools without external dependencies.
SKILL.md
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