# How to Check if a File Was Made with Claude

> Published 2026-09-03 · https://www.promptzone.com/neha_wu/how-to-check-if-a-file-was-made-with-claude-496

A new discussion on [Hacker News](https://claude.com/check-content) examines tools and techniques to determine whether a file or document was produced by Claude.

The thread has accumulated **149 points and 110 comments**, with users sharing scripts, API checks, and statistical markers that distinguish Claude output from other models.

## What Detection Methods Exist

Users describe several approaches. One method queries Claude's own API with a hash or excerpt to check for known generation fingerprints. Another analyzes token distribution patterns that appear more frequently in Claude responses than in GPT or Gemini text.

A third technique scans for embedded metadata strings that Anthropic systems sometimes leave in exported files.

## Key Numbers from the Thread

Early tests shared in the comments report **82% accuracy** on plain text files under 2,000 tokens. Accuracy drops to **61%** once the text passes through heavy editing or translation tools.

Memory usage for the open-source scanner mentioned most often stays under **340 MB** when run locally.

## How to Try the Main Tool

Install the community script referenced in the thread with a single pip command. Point it at a target file and it returns a probability score plus highlighted sections.

The same repository includes a lightweight web demo that accepts direct file uploads without local installation.

## Pros and Cons

- Works offline after initial download
- Provides line-level highlights rather than a single score
- Accuracy falls sharply on heavily revised text
- No official Anthropic endorsement or API guarantee

## Alternatives and Comparison

| Tool | Accuracy on Claude text | Local run | License |
|------|-------------------------|-----------|---------|
| HN script | 82% | Yes | MIT |
| GPTZero | 71% | No | Paid |
| Originality.ai | 78% | No | Paid |
| ZeroGPT | 65% | Yes | Free |

The local HN script leads on speed and cost for repeated checks.

## Who Should Use This

Developers auditing large codebases or writers verifying client submissions benefit most. Teams already using multiple LLMs should skip it if their workflow includes heavy post-editing, where detection rates drop below usable thresholds.

## Bottom Line

The Hacker News thread surfaces the first practical, locally runnable method specifically tuned for Claude output, giving practitioners a concrete starting point for verification tasks.

The discussion shows demand for reliable, model-specific detectors will keep growing as more organizations require provenance checks on AI-produced material.