AI output confidence language analyzer
Large language models have a calibration problem: they often phrase uncertain or even fabricated claims with the exact same authority as well-established facts, and elsewhere drown genuinely useful answers in qualifiers. This analyzer scans AI-generated text for both failure modes — false certainty (assertive claims with no hedging) and excessive hedging (so many qualifiers the information is useless) — and shows you where to rebalance the tone.
How it works
The tool runs entirely in your browser. It splits your text into sentences and checks each one for two signal sets. Hedging markers (such as “might,” “possibly,” “it seems,” “I’m not certain”) indicate softened language, while strong-assertion markers (such as “definitely,” “always,” “guaranteed,” “without a doubt”) indicate confidence. A sentence that makes a checkable factual claim with zero hedging and an assertive marker is flagged as potentially over-confident; a sentence stacked with multiple hedges is flagged as over-hedged. You get counts, the offending phrases, and the sentence each appears in.
Tips and notes
This is a linguistic signal, not a fact-checker — a confidently worded sentence can still be true, and a hedged one can still be wrong. Use the over-confident flags as a checklist of claims to verify, and the over-hedged flags as candidates to tighten. Aim for calibrated output: state solid facts plainly, and reserve hedging for things that are genuinely uncertain. Re-run after editing to confirm the balance improved.