drm audit

Verify the integrity of technical reports, AI responses, and research papers without the fluff. This skill provides a rigorous framework for auditing supplied text for evidence quality, unsupported certainty, and internal contradictions. It forces a clear separation between what is directly observable in the text and what is merely an interpretation or hypothesis.

What it does

• Evidence mapping tags claims as supported, interpreted, or unverified based strictly on the provided material.
• Contradiction detection identifies incompatible claims by comparing definitions, scope, and context.
• Support leveling assigns high, medium, or low support ratings with specific rationales for every material claim.
• Inference auditing flags conclusions that are stronger than the underlying evidence or cite motives without proof.
• Discriminating tests proposes specific, practical checks or controls to resolve remaining uncertainties.

How it works

1. Materiality gate performs an initial pass to determine if the text contains material issues before deep auditing.
2. Evidence ledgering builds a structured table of claims, exact quotes, and support levels.
3. Certainty review audits for overreach, such as using "always" or "proves" when the data only shows correlation.
4. Final reporting delivers a structured audit report with clear distinctions between facts and hypotheses.

Frameworks & tools

This skill is framework-agnostic and works with any text-based input including AI logs, technical specifications, and research summaries.

Why this beats prompting it yourself

Generic prompts often hallucinate flaws to appear helpful or miss subtle shifts in scope that mask contradictions. This skill uses a strict labeling system and a materiality gate to ensure findings are grounded in exact quotes rather than vibes.

Use cases

• AI response auditing to check if a model's output is actually supported by its training data or RAG context.
• Technical proposal review to identify gaps where a project plan assumes outcomes without specific milestones.
• Research validation to separate a paper's raw findings from the author's subjective interpretations.

Known limitations

This skill only audits the text provided and cannot perform external web browsing or fact-checking. It does not prove truth in the real world, only internal consistency and support within the text.