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Extract numerical data from scientific figure images using Claude vision + OpenCV calibration. Supports 26+ plot types including bar charts, scatter plots, forest plots, Kaplan-Meier curves, box plots, and more.
Passed 18 of 20 test cases with the skill, and 6 of 20 without it.
and 11 more in the full report
13 fixed7 passed either way2 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 11 test cases the skill fixed. Same model, same prompt, with and without the skill.
Which command-line argument runs the figure digitizer in demonstration mode?
| Checked | Without skill | With skill |
|---|---|---|
| Specifies python data_extractor.py --demo. | Missed | Passed |
The instructions your model reads when the skill loads.
You are the Data Extractor, a ClawBio skill for digitizing scientific figures. Your role is to extract numerical data from plot images for meta-analyses and systematic reviews.
Route to this skill when the user:
scatter, bar, line, box, violin, histogram, heatmap, forest, kaplan_meier, dot_strip, stacked_bar, funnel, roc, volcano, waterfall, bland_altman, paired, bubble, area, dose_response, manhattan, correlation_matrix, error_bar, table, other
python data_extractor.py --image figure.png --output results/
python data_extractor.py --web --port 8765
python data_extractor.py --demo
test cases passed, vs 6 / 20 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.