Agent skill

data-extractor

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.

View SKILL.md on GitHub Repository
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Forks 57

Install this agent skill to your Project

npx add-skill https://github.com/beita6969/ScienceClaw/tree/main/skills/data-extractor

Metadata

Additional technical details for this skill

openclaw 
{
    "os": [
        "darwin",
        "linux"
    ],
    "emoji": "\ud83d\udcca",
    "always": false,
    "install": [
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            "package": "anthropic"
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            "bins": [],
            "kind": "pip",
            "package": "opencv-python-headless"
        },
        {
            "bins": [],
            "kind": "pip",
            "package": "numpy"
        },
        {
            "bins": [],
            "kind": "pip",
            "package": "Pillow"
        },
        {
            "bins": [],
            "kind": "pip",
            "package": "pydantic"
        },
        {
            "bins": [],
            "kind": "pip",
            "package": "fastapi"
        },
        {
            "bins": [],
            "kind": "pip",
            "package": "uvicorn"
        }
    ],
    "homepage": "https://github.com/ClawBio/ClawBio",
    "requires": {
        "env": [
            "ANTHROPIC_API_KEY"
        ],
        "bins": [
            "python3"
        ],
        "config": []
    }
}

SKILL.md

📊 Data Extractor

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.

When to Use This Skill

Route to this skill when the user:

  • Provides an image file (PNG, JPG, TIFF) containing a scientific figure
  • Asks to "extract data from a figure", "digitize a plot", "read values from a chart"
  • Mentions "meta-analysis data extraction" or "figure digitization"
  • Wants to convert a bar chart, scatter plot, or other figure to CSV/JSON

Capabilities

Supported Plot Types (26)

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

Pipeline (4 phases)

  1. Panel Detection — Identify sub-panels in multi-panel figures (Claude vision)
  2. Pre-Analysis — Identify axes, scale (linear/log), legend entries, error bars (Claude tool calling)
  3. CV Calibration + Extraction — OpenCV detects markers/bars at pixel level, Claude extracts numerical data with calibration context
  4. Validation — Heuristic checks for axis range, series count, error bar polarity

Output Formats

  • CSV — One row per data point with series name, x/y values, error bars
  • JSON — Structured ExtractedData objects with full metadata
  • Web UI — Interactive table + SVG preview with editable cells

Usage

CLI

bash
python data_extractor.py --image figure.png --output results/
python data_extractor.py --web --port 8765
python data_extractor.py --demo

API (importable)

python
from api import run
result = run(options={"image_path": "figure.png", "output_dir": "results/"})

Web UI

Launch with --web flag. Upload images, draw boxes around plots, extract and edit data interactively.

Input Formats

  • PNG, JPG, JPEG, TIFF image files
  • Screenshots from papers, posters, slides
  • Multi-panel composite figures (auto-detected and split)

Notes

  • Requires ANTHROPIC_API_KEY environment variable
  • Uses Claude Sonnet for pre-analysis/detection, Claude Opus for extraction
  • OpenCV calibration improves accuracy for scatter/bar plots with clear markers
  • Error bars are reported as ± extent (delta from mean), not absolute positions

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