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Extract pixel-level data from an image of a chart or graph and produce a structured data table.
Install Chart Data Extractor
$ npx skills add mohitagw15856/pm-claude-skills --skill chart-data-extractor -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install mohitagw15856/pm-claude-skills chart-data-extractor --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/chart-data-extractor .claude/skills/chart-data-extractor && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "chart-data-extractor" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/chart-data-extractor into .claude/skills/chart-data-extractor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chart-data-extractor", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/chart-data-extractorType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add mohitagw15856/pm-claude-skills --skill chart-data-extractor -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install mohitagw15856/pm-claude-skills chart-data-extractor --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/chart-data-extractor .agents/skills/chart-data-extractor && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "chart-data-extractor" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/chart-data-extractor into .agents/skills/chart-data-extractor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chart-data-extractor", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add mohitagw15856/pm-claude-skills --skill chart-data-extractor -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install mohitagw15856/pm-claude-skills chart-data-extractor --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/chart-data-extractor .cursor/skills/chart-data-extractor && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "chart-data-extractor" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/chart-data-extractor into .cursor/skills/chart-data-extractor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chart-data-extractor", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/mohitagw15856/pm-claude-skills.git --path skills/chart-data-extractor--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add mohitagw15856/pm-claude-skills --skill chart-data-extractor -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install mohitagw15856/pm-claude-skills chart-data-extractor --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/chart-data-extractor .gemini/skills/chart-data-extractor && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "chart-data-extractor" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/chart-data-extractor into .gemini/skills/chart-data-extractor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chart-data-extractor", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install mohitagw15856/pm-claude-skills chart-data-extractorInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add mohitagw15856/pm-claude-skills --skill chart-data-extractor -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/chart-data-extractor .github/skills/chart-data-extractor && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "chart-data-extractor" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/chart-data-extractor into .github/skills/chart-data-extractor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chart-data-extractor", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add mohitagw15856/pm-claude-skills --skill chart-data-extractor -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install mohitagw15856/pm-claude-skills chart-data-extractor --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/chart-data-extractor .opencode/skills/chart-data-extractor && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "chart-data-extractor" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/chart-data-extractor into .opencode/skills/chart-data-extractor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chart-data-extractor", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
chart-data-extractor- GitHub stars
- 1.4k
- Token cost
- ~1.2k tokens
- SKILL.md length
- 588 words
- Files
- 1
- Skills in repo
- 1,322
- Repo updated
- First seen
- Licence
- MIT
At a glance
Extract pixel-level data from an image of a chart or graph and produce a structured data table.
- Works in 7 steps: Chart Identification → Extracted Data Table → Confidence Levels → …
- Asked to extract data from a chart image
- SKILL.md covers Required Inputs, Output Structure, Quality Checks and Anti-Patterns, plus 2 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Chart Data Extractor is an agent skill from mohitagw15856/pm-claude-skills. 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.
Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Marketing & SEO, covering Schema markup and Transcription. The repository describes itself as: 1255 professional Agent Skills for Claude, ChatGPT, Gemini, Cursor & Codex — PRDs, postmortems, leases, medical bills, layoffs, go-bags, new countries. Plain markdown, MIT, in… The licence is MIT.
When your agent uses it
- Asked to extract data from a chart image
- Transcribe numbers from a graph
- Digitise a chart
- Turn a screenshot of data into a table
Example prompts
- “/chart-data-extractor”
Requirements
- Python 3
Workflow steps
7 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit 1cbf1f0. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are csv).
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Chart Data Extractor loads about 1.2k tokens when it runs. Until then it costs about 110 tokens; SKILL.md has 588 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from mohitagw15856/pm-claude-skills at commit 1cbf1f0, republished under its MIT licence (© mohitagw15856). 588 words, ~1,184 tokens.
Download SKILL.mdSave it as
.claude/skills/chart-data-extractor/SKILL.md (or your agent's skills folder).- name
- chart-data-extractor
- description
- 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.
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. Confidence Levels
For each data point or series, flag confidence:
- High confidence: data points where the value is clearly readable against gridlines or labels
- Medium confidence: data points where the value is interpolated between gridlines
- Low confidence: data points where the value is ambiguous or overlaps with other elements
Low-confidence points should be explicitly listed — not silently included in the main table.
4. Notable Observations
Observations that the data itself reveals:
- Peak value: [Value, when, in which series]
- Lowest value: [Value, when, in which series]
- Largest delta between series: [Details]
- Any anomalies or outliers visible in the chart
5. Reconstructed Source
CSV format for direct use:
[x_axis],[series_1],[series_2]
[value],[value],[value]6. Assumptions and Caveats
- Grid resolution: [How precisely values could be read — e.g. "Y-axis has major gridlines every 10 units, minor every 2"]
- Interpolation used: [Any values that required estimating between gridlines]
- Unclear data: [Anything in the chart that could not be read reliably]
- Axis scale: [Linear/logarithmic/etc — note if not obvious]
7. Follow-up Options
Ask the user which of these they want:
- Rebuild the chart in a specified format (Excel formula, Python matplotlib, D3, etc.)
- Produce a narrative description of what the chart shows
- Compare this data against another chart or source
- Flag potentially misleading visual choices in the original (truncated axes, misleading scales, etc.)
Show full SKILL.md (217 more words)Show less
Quality Checks
- Every extracted number specifies which series it belongs to
- Confidence levels are explicit for ambiguous points
- Low-confidence values are flagged separately, not silently included
- Assumptions about axis scale and interpolation are stated
- CSV output is clean and directly usable
Anti-Patterns
- Do not silently include low-confidence data points in the main table — flag them separately so the user knows which values to verify
- Do not assume a linear scale without confirming it — logarithmic axes make extracted values incorrect by orders of magnitude if misread
- Do not report extracted values with false precision — if the chart's Y-axis only shows gridlines every 10 units, a reported value of 37 is invented, not extracted
- Do not omit the assumptions and caveats section — partial image quality, overlapping bars, or unlabelled axes must be disclosed
Example Trigger Phrases
- "Extract the data from this chart"
- "Transcribe the numbers in this graph"
- "Turn this chart image into a spreadsheet"
- "Digitise this chart so I can rebuild it"
- "What are the exact values in this bar chart?"
Why This Works Better on Opus 4.7
Earlier models struggled with pixel-level data transcription from charts, often hallucinating values or misreading gridline positions. Opus 4.7 uses a higher image resolution (2576px vs 1568px) with coordinates mapping 1:1 to pixels, making chart data extraction reliable for practical use.
© mohitagw15856, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in skills/chart-data-extractor of mohitagw15856/pm-claude-skills.
Open the folder on GitHubat commit 1cbf1f0
Compare with similar skills
Chart Data Extractor next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Chart Data Extractor this skillmohitagw15856/pm-claude-skills | 1.4k | — | ~1.2k | Automated safety check: Pass | MIT | |
| SEO Setupalisamadiii/Portfolio | 180 | — | ~1.7k | Automated safety check: Pass | None | |
| Nuxt SEO Best Practicesvinayakkulkarni/nxui | 212 | — | ~819 | Automated safety check: Pass | MIT | |
| Gaik ToolkitGAIK-project/gaik-toolkit | 100 | — | ~5.7k | Automated safety check: Pass | MIT | |
| Growth ReportInfrasity-Labs/dev-gtm-claude-skills | 139 | — | ~4k | Automated safety check: Pass | MIT | |
| SEO GeoReScienceLab/opc-skills | 1.8k | 4 repos | ~2.1k | Automated safety check: Pass | Apache-2.0 |
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Related
Questions about Chart Data Extractor
What does Chart Data Extractor do?
Extract pixel-level data from an image of a chart or graph and produce a structured data table. Chart Data Extractor is an agent skill from mohitagw15856/pm-claude-skills. Extract pixel-level data from an image of a chart or graph and produce a structured data table.
When should I use Chart Data Extractor?
Chart Data Extractor fits situations like: asked to extract data from a chart image; transcribe numbers from a graph; digitise a chart; turn a screenshot of data into a table.
How do I install Chart Data Extractor in Claude Code?
Run `npx skills add mohitagw15856/pm-claude-skills --skill chart-data-extractor -a claude-code`. Or copy the skill folder (skills/chart-data-extractor in mohitagw15856/pm-claude-skills) into .claude/skills/chart-data-extractor in your project. Claude Code loads it when a task matches its description.
How do I install Chart Data Extractor in Codex?
Run `npx skills add mohitagw15856/pm-claude-skills --skill chart-data-extractor -a codex`. Or copy the skill folder (skills/chart-data-extractor in mohitagw15856/pm-claude-skills) into .agents/skills/chart-data-extractor in your project. Codex loads it when a task matches its description.
Can I use Chart Data Extractor in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mohitagw15856/pm-claude-skills --skill chart-data-extractor -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/chart-data-extractor, .gemini/skills/chart-data-extractor, .github/skills/chart-data-extractor and .opencode/skills/chart-data-extractor in your project.
What does Chart Data Extractor need to run?
SKILL.md names no scripts, command-line tools or credentials: Chart Data Extractor is instructions for the agent only. Our summary lists: Python 3.
Does Chart Data Extractor access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Chart Data Extractor safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Chart Data Extractor use?
Chart Data Extractor is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Chart Data Extractor use?
About 1.2k tokens (SKILL.md is roughly 4.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Chart Data Extractor?
Skills that share tags, products or a category with Chart Data Extractor: SEO Setup (alisamadiii/Portfolio, 180 stars), Nuxt SEO Best Practices (vinayakkulkarni/nxui, 212 stars), Gaik Toolkit (GAIK-project/gaik-toolkit, 100 stars) and Growth Report (Infrasity-Labs/dev-gtm-claude-skills, 139 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Chart Data Extractor?
mohitagw15856 (a GitHub user) maintains it in mohitagw15856/pm-claude-skills, which has 1,431 GitHub stars. The repository holds 1,322 skills in this directory. The repository was last updated on October 7, 2026.
Source: mohitagw15856/pm-claude-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.