How to use this text tool
- Paste or upload your text.
- Choose the analysis mode or preset.
- Run the tool and review the quality score, detected issues, and exportable report.
Find likely passive voice sentences using a practical be-verb plus participle heuristic for academic drafts.
Passive Voice Heuristic Checker turns pasted academic text into practical diagnostics with counts, warnings, and a concise improvement signal.
Use the output as a fast editorial check. Human review is still recommended for final academic submission.
Example: paste a paragraph or reference section, run Passive Voice Heuristic Checker, then use the generated report to revise length, formatting, flow, or consistency.
All processing runs locally in the browser with JavaScript. The page does not need a server-side text upload to calculate results.
Pattern-based academic tools can produce false positives, especially with citations, passive voice, and dialogue detection.
Paste the relevant text into Passive Voice Heuristic Checker, choose the options that match your goal, and run the tool. Review the output and metrics to identify passive voice in academic writing before copying or downloading the result.
Passive Voice Heuristic Checker runs locally in the browser. Review the tool-specific metrics and warnings before copying or downloading the result.
Test this case in Passive Voice Heuristic Checker with a short sample first, then apply the same settings to the full text after confirming the output.
Passive Voice Heuristic Checker reports the tool-specific output and supporting metrics directly in your browser. For “What percentage of passive voice is acceptable?”, use the displayed result, interpretation, and example together rather than relying on one number alone.
Passive Voice Heuristic Checker runs locally in the browser. Review the tool-specific metrics and warnings before copying or downloading the result.
| Module | Function |
|---|---|
| Input parser | Normalizes pasted or uploaded academic text |
| Pattern detector | Finds tool-specific writing signals |
| Quality score | Summarizes readiness on a 0–100 scale |
| Export module | Creates TXT, CSV, and JSON reports |