POV Consistency Checker
Split a manuscript into scenes and check the point of view in each — pronoun counts, dominant POV, filter verbs and head-hopping between viewpoint characters.
Paste a chapter above to see the point of view scene by scene.
This counts pronouns from a fixed list and flags roughly forty interior-thought verbs — it does not parse grammar, so first-person pronouns inside dialogue will show up in a third-person scene, which is normal and expected. Treat the flags as places to look, not errors. Nothing is uploaded; the analysis runs entirely in your browser.
What is the POV Consistency Checker?
POV Consistency Checker splits your manuscript into scenes at the separator you choose, counts first-, second- and third-person pronouns in each one, and reports the dominant point of view scene by scene.
- Per-scene first-, second- and third-person pronoun counts and a dominant POV verdict
- Four ways to split scenes, including a custom separator
- Target POV set manually or detected automatically across the whole text
- About forty interior-thought filter verbs highlighted in the scene text
- Head-hopping flag when two named viewpoint characters both get interiority in one scene
- Optional it / its counting, off by default so neuter pronouns don't skew the result
How to use the POV Consistency Checker
- 1
Paste a chapter or a whole manuscript into the text box.
- 2
Choose how scenes are separated — blank line, a scene-break marker, chapter headings or your own text.
- 3
Set the target point of view, or leave it on auto to use whichever POV dominates the whole text.
- 4
Optionally list your viewpoint characters, comma separated, to enable the mixed-interiority check.
- 5
Read the scene table, then work through the flagged scenes with the filter verbs highlighted in context.
About the POV Consistency Checker
POV Consistency Checker splits your manuscript into scenes at the separator you choose, counts first-, second- and third-person pronouns in each one, and reports the dominant point of view scene by scene. Any scene whose POV differs from your target is highlighted, as is any scene that mixes two persons heavily.
It also counts interior-thought filter verbs — felt, wondered, realised, noticed and about forty more — and, if you name your viewpoint characters, flags scenes where two of them are given interiority at once, which is the classic head-hopping symptom.
This counts words from fixed lists rather than parsing grammar, so first-person pronouns inside dialogue will appear in a third-person scene. Treat the flags as places to look. Nothing is uploaded; the analysis runs in your browser.
Frequently asked questions
What is head-hopping?
Slipping from one character's interiority into another's inside a single scene, without a break to signal the change. Readers usually feel it as a small jolt of confusion. The tool flags a scene when two of your named viewpoint characters both appear next to interior-thought verbs.
What are filter verbs and why do they matter?
Verbs like felt, saw, wondered and realised that put the narrator between the reader and the experience — “she felt the cold” instead of “the cold bit through her coat”. They are not errors, but a high density of them usually means the prose can be tightened.
Why does my third-person scene show first-person pronouns?
Almost always because of dialogue. Characters say “I” regardless of the narrative point of view. The tool counts words rather than parsing grammar, so read the counts as a shape rather than a verdict — a third-person scene with some first-person pronouns is completely normal.
Does it detect third-person limited versus omniscient?
No. Both use the same pronouns, and telling them apart needs an understanding of whose thoughts the narration can reach. What the tool can tell you is whether more than one character's interiority appears in a single scene, which is the practical question for limited POV.
Is my manuscript sent anywhere?
No. Everything is analysed by JavaScript in your browser and your text never leaves your device.
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