Agent skill · Data & Analytics

chart-data-extractor

Extract pixel-level data from an image of a chart or graph and produce a structured data table. Use when asked to extract data from a chart image, transcribe numbers from a graph, digitise a chart, or turn a screenshot of data into a table. Produces a structured table with extracted values, confidence levels, and a reconstructed chart source. Best used with Claude Opus 4.7 or newer for reliable chart data extraction.

mohitagw15856github.com/mohitagw15856GitHub ↗
claude-codecursorMIT
Install
npx skills add mohitagw15856/pm-claude-skills --skill chart-data-extractor --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 5 KB
Bundled scripts: none
Path: skills/chart-data-extractor/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 1,255
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Chart Data Extractor Skill Extracts data from images of charts and graphs — bar charts, line charts, pie charts, scatter plots, and tables in images — producing a structured data table that can be used in spreadsheets or rebuilt in any charting tool. Built to leverage Opus 4.7 pixel-level image analysis capabilities. ## Required Inputs Ask the user for these if not provided: - **The chart image** (upload a screenshot or image file) - **Chart type** (if ambiguous — bar / line / pie / scatter / other) - **What matters most** (approximate trends / precise values / specific data points / categorisation) - **Known axis values** (optional — if the user knows the max/min values to anchor the extraction) ## Output Structure ### 1. Chart Identification | Attribute | Value | |---|---| | Chart type | [Bar / Line / Pie / Scatter / Area / Other] | | Chart title (if visible) | [Title text] | | X-axis label | [Label + unit] | | Y-axis label | [Label + unit] | | Number of series | N | | Legend categories | [List] | | Data period (if time-based) | [Start — End] | ### 2. Extracted Data Table | [X axis] | [Series 1] | [Series 2] | ... | |---|---|---|---| | [Value] | [Value] | [Value] | | ### 3. Con

What's inside
Steps it walks through
  1. Required Inputs
  2. Output Structure
  3. 1. Chart Identification
  4. 2. Extracted Data Table
  5. 3. Confidence Levels
  6. 4. Notable Observations
  7. 5. Reconstructed Source
  8. 6. Assumptions and Caveats
  9. 7. Follow-up Options
  10. Quality Checks
  11. Anti-Patterns
  12. Example Trigger Phrases
  13. Why This Works Better on Opus 4.7
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About this skill
What does the chart-data-extractor skill do?

Extract pixel-level data from an image of a chart or graph and produce a structured data table. Use when asked to extract data from a chart image, transcribe numbers from a graph, digitise a chart, or turn a screenshot of data into a table. Produces a structured table with extracted values, confidence levels, and a reconstructed chart source. Best used with Claude Opus 4.7 or newer for reliable chart data extraction.

How do I install it?

Run `npx skills add mohitagw15856/pm-claude-skills --skill chart-data-extractor --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From mohitagw15856/pm-claude-skills, a repository with 1,255 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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