proposition-audit-anthony-searle
Post-hoc verification and trust audit of AI-generated factual and interpretive claims. Classifies claims by type and salience, routes them to domain-appropriate sources, scores trustworthiness on a tiered scale with an Interpolated verdict for plausible-but-unsupported detail, and assesses rhetorical fairness on interpretive claims. Designed for clinical-negligence and healthcare-law practice in England and Wales, with general applicability beyond.
npx skills add lawve-ai/awesome-legal-skills --skill proposition-audit-anthony-searle --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Proposition Audit — AI Output Trust Verification ## Profile - **Jurisdiction:** England and Wales (the maintained domain-routing profile; other jurisdictions illustrated under Step 2). - **Practice area:** Clinical negligence and healthcare law (the maintained example domain; the methodology generalises to any field where AI-drafted factual content needs structured verification). - **Intended user:** A practitioner verifying AI-generated factual or interpretive content before professional reliance — publication, court use, formal external use, or internal reliance. ## Purpose AI-generated research, statistics, citations, and factual claims require structured verification before professional use. This skill provides a systematic post-hoc audit — classifying each claim by type and salience, searching domain-appropriate sources, scoring trustworthiness transparently, and flagging what needs attention. This complements rather than replaces rigour during generation. It is an independent verification layer applied to completed output. ## The Verification Process ### Step 1: Agree the Threshold Before beginning verification, ask what minimum standard applies to this use case. Offer thes
- Profile
- Purpose
- The Verification Process
- Step 1: Agree the Threshold
- Step 2: Extract and Classify Claims
- Step 3: Search for Sources
- Step 4: Score Each Claim
- Step 5: Produce the Audit Report
- Limitations and assumptions
- Principles
- Example
What does the proposition-audit-anthony-searle skill do?
Post-hoc verification and trust audit of AI-generated factual and interpretive claims. Classifies claims by type and salience, routes them to domain-appropriate sources, scores trustworthiness on a tiered scale with an Interpolated verdict for plausible-but-unsupported detail, and assesses rhetorical fairness on interpretive claims. Designed for clinical-negligence and healthcare-law practice in England and Wales, with general applicability beyond.
How do I install it?
Run `npx skills add lawve-ai/awesome-legal-skills --skill proposition-audit-anthony-searle --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From lawve-ai/awesome-legal-skills, a repository with 618 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.