Manuscript Analysis Free · in-browser · optional cloud history

Show Don't Tell Hints

Flags telling phrases — emotion labels, mental verbs, and summarised action like “told him about…” — and names the text it scored. A zero means no pattern matched, not a clean verdict.

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Paste your text above, then click Analyze — or use Try sample for a quick demo.

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About this tool

Telling names a feeling or sums up an action instead of playing it out. This checker matches telling phrases in your paste — emotion labels (felt angry, was nervous), "a wave of…" feelings, mental verbs (she realized, he wondered), "seemed to be", and summarised action (told him about, explained how, turns the question on, spent the next hour) — highlights each one, and says which text it scored: the chapter heading if there is one, otherwise the opening words. A zero means none of these patterns turned up, not that the scene shows rather than tells. The scan runs in your browser.

What you can do

  • Emotion labels: felt angry, was nervous, were devastated
  • Abstract feelings: a wave of…, a pang of…, a surge of…
  • Mental verbs: she realized, he wondered, they knew
  • Summarised action: told him about…, explained how…, turns the question on…, spent the next hour…
  • "Seemed to be" and "appeared to be" hedges
  • Count per 1,000 words, a breakdown by pattern, and in-context highlights
  • Names the text it scored (chapter heading or opening words) and its word count

Why manuscript analysis matters for fiction

Rule-based analyzers catch patterns human eyes skim past—especially in AI drafts where filter words, adverbs, and passive voice cluster predictably. Use metrics to prioritize revision, not to flatten your voice. Run a chapter first, fix the worst offenders, then scan the full manuscript.

Five-pass revision order · AI manuscript editing · Manuscript cleanup

How to use it

  1. Paste your scene or chapter into the text area.
  2. Click Analyze to scan for telling patterns.
  3. Review highlighted emotion labels and mental verbs.
  4. Replace telling with action, dialogue, or sensory detail.
  5. Re-scan to reduce telling density per 1,000 words.

Tips for fiction authors

  • Replace "He was angry" with physical cues: clenched jaw, white knuckles, a raised voice. Readers infer the emotion.
  • Summary telling is fine for transitions: "The next three days passed in silence." Not every moment needs to be dramatized.
  • AI models default to labeling emotions because it is efficient. Your revision pass is where scenes come alive.
  • Focus on high-stakes scenes first. Telling in a quiet transition matters less than telling during your climax.
  • Pair show-don't-tell fixes with the sensory detail scanner — one concrete smell or texture often replaces a paragraph of telling.

Related guides

Why AI Writes Every Character Wanting the Same Thing How to Use AI to Diagnose and Fix Sentence-Level Monotony Why AI Resolves Every Scene's Emotional Beat Too Neatly Use AI to Find Where Scenes Overstay Their Welcome

Common questions
What counts as "telling"?

Phrases that label a feeling ("she felt angry", "he was devastated", "a wave of sadness"), report a thought ("she realized"), or sum up an action instead of playing it out ("she told him about the fire", "spent the next three hours"). The tool matches those phrase patterns; it does not read every sentence for meaning, so read the scene for other summaries too.

Is all telling bad?

No. Summary telling has its place. This tool helps you find clusters to convert in important scenes.

Why do AI drafts tell so much?

Models summarize internal states efficiently. Showing requires concrete detail — this checker marks where to add it.

Is my manuscript uploaded?

No. Show-don't-tell scanning runs entirely in your browser on Entangled Text.

Should I fix telling before filter words?

Many authors run Manuscript Cleanup first, then use this tool on chapters with the highest telling density.

Why did my chapter score 0?

None of the phrase patterns turned up. That is not a verdict that the chapter shows rather than tells — a summary worded another way will not match. The results name the text that was scored (its chapter heading or opening words) and its word count, so you can check it read the chapter you meant.

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