Create HTML Embed
adithya-s-k/FineEnvs
Create self-contained D3 HTML embed charts for the research article template.
A skill your agent uses when creating charts, plots, or dashboards.
Install Visualization Selection
$ npx skills add aiming-lab/MetaClaw --skill visualization-selection -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install aiming-lab/MetaClaw visualization-selection --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/aiming-lab/MetaClaw.git skills-src && mkdir -p .claude/skills && cp -r skills-src/memory_data/skills/visualization-selection .claude/skills/visualization-selection && 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 "visualization-selection" agent skill from https://github.com/aiming-lab/MetaClaw/tree/main/memory_data/skills/visualization-selection into .claude/skills/visualization-selection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "visualization-selection", 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/aiming-lab/MetaClaw/tree/main/memory_data/skills/visualization-selectionType 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 aiming-lab/MetaClaw --skill visualization-selection -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install aiming-lab/MetaClaw visualization-selection --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aiming-lab/MetaClaw.git skills-src && mkdir -p .agents/skills && cp -r skills-src/memory_data/skills/visualization-selection .agents/skills/visualization-selection && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "visualization-selection" agent skill from https://github.com/aiming-lab/MetaClaw/tree/main/memory_data/skills/visualization-selection into .agents/skills/visualization-selection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "visualization-selection", 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 aiming-lab/MetaClaw --skill visualization-selection -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install aiming-lab/MetaClaw visualization-selection --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aiming-lab/MetaClaw.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/memory_data/skills/visualization-selection .cursor/skills/visualization-selection && 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 "visualization-selection" agent skill from https://github.com/aiming-lab/MetaClaw/tree/main/memory_data/skills/visualization-selection into .cursor/skills/visualization-selection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "visualization-selection", 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/aiming-lab/MetaClaw.git --path memory_data/skills/visualization-selection--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 aiming-lab/MetaClaw --skill visualization-selection -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install aiming-lab/MetaClaw visualization-selection --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aiming-lab/MetaClaw.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/memory_data/skills/visualization-selection .gemini/skills/visualization-selection && 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 "visualization-selection" agent skill from https://github.com/aiming-lab/MetaClaw/tree/main/memory_data/skills/visualization-selection into .gemini/skills/visualization-selection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "visualization-selection", 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 aiming-lab/MetaClaw visualization-selectionInstalls 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 aiming-lab/MetaClaw --skill visualization-selection -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/aiming-lab/MetaClaw.git skills-src && mkdir -p .github/skills && cp -r skills-src/memory_data/skills/visualization-selection .github/skills/visualization-selection && 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 "visualization-selection" agent skill from https://github.com/aiming-lab/MetaClaw/tree/main/memory_data/skills/visualization-selection into .github/skills/visualization-selection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "visualization-selection", 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 aiming-lab/MetaClaw --skill visualization-selection -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install aiming-lab/MetaClaw visualization-selection --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aiming-lab/MetaClaw.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/memory_data/skills/visualization-selection .opencode/skills/visualization-selection && 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 "visualization-selection" agent skill from https://github.com/aiming-lab/MetaClaw/tree/main/memory_data/skills/visualization-selection into .opencode/skills/visualization-selection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "visualization-selection", 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
visualization-selection- GitHub stars
- 3.5k
- Token cost
- ~213 tokens
- SKILL.md length
- 75 words
- Files
- 1
- Skills in repo
- 36
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when creating charts, plots, or dashboards.
- Creating charts
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Tasks that involve Data visualization
What it does
Visualization Selection is an agent skill from aiming-lab/MetaClaw. Use this skill when creating charts, plots, or dashboards. Choose the visualization type that best communicates the data relationship before writing any plotting code.
Its SKILL.md is about 210 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 Data & Analytics, covering Data visualization. The repository describes itself as: 🦞 Just talk to your agent — it learns and EVOLVES 🧬. The licence is MIT.
When your agent uses it
- Creating charts
- Tasks that involve Data visualization
Example prompts
- “/visualization-selection”
What it can do on your machine
Read from SKILL.md and the folder at commit 922caf3. 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.
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
Visualization Selection loads about 213 tokens when it runs. Until then it costs about 48 tokens; SKILL.md has 75 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 aiming-lab/MetaClaw at commit 922caf3, republished under its MIT licence (© aiming-lab). 75 words, ~213 tokens.
Download SKILL.mdSave it as
.claude/skills/visualization-selection/SKILL.md (or your agent's skills folder).- name
- visualization-selection
- description
- Use this skill when creating charts, plots, or dashboards. Choose the visualization type that best communicates the data relationship before writing any plotting code.
- category
- data_analysis
Visualization Selection Guide
| Goal | Chart Type |
|---|---|
| Compare categories | Bar chart (horizontal if many labels) |
| Show distribution | Histogram, box plot, violin plot |
| Show trend over time | Line chart |
| Show correlation | Scatter plot, heatmap |
| Show part-to-whole | Pie (<=5 slices), stacked bar |
Principles:
- Label axes and include units.
- Use color purposefully — not just for decoration.
- Avoid 3D charts; they distort perception.
- Start y-axis at 0 for bar charts (truncated bars mislead).
- Use a colorblind-safe palette (e.g.,
viridis,colorbrewer).
© aiming-lab, 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 memory_data/skills/visualization-selection of aiming-lab/MetaClaw.
Open the folder on GitHubat commit 922caf3
Compare with similar skills
Visualization Selection 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 |
|---|---|---|---|---|---|---|
| Visualization Selection this skillaiming-lab/MetaClaw | 3.5k | — | ~213 | Automated safety check: Pass | MIT | |
| Create HTML Embedadithya-s-k/FineEnvs | 421 | — | ~1.1k | Automated safety check: Pass | Apache-2.0 | |
| Scholar Lingjoshzyj/open-scholar-skill | 167 | — | ~6.7k | Automated safety check: Pass | Custom licence | |
| Bio Data Visualization Dimensionality Reduction PlotsGPTomics/bioSkills | 1.2k | 2 repos | ~4.8k | Automated safety check: Pass | MIT | |
| Bio Data Visualization Ggplot2 FundamentalsGPTomics/bioSkills | 1.2k | 2 repos | ~2.8k | Automated safety check: Pass | MIT | |
| Metagenomic Krona Chartaipoch/medical-research-skills | 2k | — | ~2.5k | Automated safety check: Pass | MIT |
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Related
Categories
Questions about Visualization Selection
What does Visualization Selection do?
A skill your agent uses when creating charts, plots, or dashboards. Visualization Selection is an agent skill from aiming-lab/MetaClaw. Use this skill when creating charts, plots, or dashboards.
When should I use Visualization Selection?
Visualization Selection fits situations like: creating charts; tasks that involve Data visualization.
How do I install Visualization Selection in Claude Code?
Run `npx skills add aiming-lab/MetaClaw --skill visualization-selection -a claude-code`. Or copy the skill folder (memory_data/skills/visualization-selection in aiming-lab/MetaClaw) into .claude/skills/visualization-selection in your project. Claude Code loads it when a task matches its description.
How do I install Visualization Selection in Codex?
Run `npx skills add aiming-lab/MetaClaw --skill visualization-selection -a codex`. Or copy the skill folder (memory_data/skills/visualization-selection in aiming-lab/MetaClaw) into .agents/skills/visualization-selection in your project. Codex loads it when a task matches its description.
Can I use Visualization Selection 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 aiming-lab/MetaClaw --skill visualization-selection -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/visualization-selection, .gemini/skills/visualization-selection, .github/skills/visualization-selection and .opencode/skills/visualization-selection in your project.
What does Visualization Selection need to run?
SKILL.md names no scripts, command-line tools or credentials: Visualization Selection is instructions for the agent only.
Does Visualization Selection 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 Visualization Selection 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 Visualization Selection use?
Visualization Selection 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 Visualization Selection use?
About 213 tokens (SKILL.md is roughly 852 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 Visualization Selection?
Skills that share tags, products or a category with Visualization Selection: Create HTML Embed (adithya-s-k/FineEnvs, 421 stars), Scholar Ling (joshzyj/open-scholar-skill, 167 stars), Bio Data Visualization Dimensionality Reduction Plots (GPTomics/bioSkills, 1.2k stars) and Bio Data Visualization Ggplot2 Fundamentals (GPTomics/bioSkills, 1.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Visualization Selection?
aiming-lab (a GitHub organization) maintains it in aiming-lab/MetaClaw, which has 3,459 GitHub stars. The repository holds 36 skills in this directory. The repository was last updated on June 7, 2026.
Source: aiming-lab/MetaClaw on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.