Tense Consistency

What It Does

Analyzes verb tenses within paragraphs to detect shifts between past and present tense. Uses NLP and morphological analysis to classify each sentence's dominant tense, then flags minority sentences that break from the paragraph's tense pattern.

Why It Matters

Unintentional tense shifts are one of the most common writing errors, especially in long manuscripts:

• Inconsistent: "She walked to the door. She opens it slowly."
• Consistent: "She walked to the door. She opened it slowly."

While some tense shifts are intentional (flashbacks, present-tense commentary), accidental shifts jolt the reader out of the narrative.

What Gets Flagged

Tense Shift

Severity: Warning

Triggered when a minority of sentences in a paragraph use a different tense from the dominant tense. The minority must be ≤ 1/3 of total sentences (to avoid flagging intentional 50/50 splits).

Example (flagged):

She walked to the door. She turned the handle. She opens it slowly. She looked inside.

Why: Three sentences use past tense; one uses present tense. The present-tense sentence is flagged.

What's Not Flagged:

• Paragraphs with fewer than 3 classifiable sentences
• Paragraphs with a 50/50 tense split (likely intentional)
• Sentences where the tense is ambiguous (no clear verb markers)

Tense Classification

The analyzer classifies tense using:

• Past: Regular -ed endings, irregular past forms (was, went, knew), past tense markers
• Present: Third-person -s forms, present markers (is, am, are, does, has)

Configuration

No configuration options.

Technical Details

• Source: prose-craft
• Scope: Paragraph-level (groups contiguous prose lines)
• Method: Verb morphology + NLP classification + dominant-tense majority analysis