Ieee Figure Table
CloudWave818/ieee-skills
Audit, redesign, generate, and improve IEEE manuscript figures, tables, captions, result presentation, plotting scripts, visual polish, hybrid Python/R plus vector-editor workflows…
Generates publication-quality scientific figures with matplotlib or seaborn through query expansion, a run-and-retry coding loop and a visual check of the rendered PNG.
Install Scientific Figure Generation
$ npx skills add lingzhi227/agent-research-skills --skill figure-generation -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install lingzhi227/agent-research-skills figure-generation --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/lingzhi227/agent-research-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/figure-generation .claude/skills/figure-generation && 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 "figure-generation" agent skill from https://github.com/lingzhi227/agent-research-skills/tree/main/skills/figure-generation into .claude/skills/figure-generation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "figure-generation", 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/lingzhi227/agent-research-skills/tree/main/skills/figure-generationType 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 lingzhi227/agent-research-skills --skill figure-generation -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install lingzhi227/agent-research-skills figure-generation --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/lingzhi227/agent-research-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/figure-generation .agents/skills/figure-generation && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "figure-generation" agent skill from https://github.com/lingzhi227/agent-research-skills/tree/main/skills/figure-generation into .agents/skills/figure-generation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "figure-generation", 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 lingzhi227/agent-research-skills --skill figure-generation -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install lingzhi227/agent-research-skills figure-generation --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/lingzhi227/agent-research-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/figure-generation .cursor/skills/figure-generation && 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 "figure-generation" agent skill from https://github.com/lingzhi227/agent-research-skills/tree/main/skills/figure-generation into .cursor/skills/figure-generation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "figure-generation", 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/lingzhi227/agent-research-skills.git --path skills/figure-generation--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 lingzhi227/agent-research-skills --skill figure-generation -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install lingzhi227/agent-research-skills figure-generation --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/lingzhi227/agent-research-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/figure-generation .gemini/skills/figure-generation && 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 "figure-generation" agent skill from https://github.com/lingzhi227/agent-research-skills/tree/main/skills/figure-generation into .gemini/skills/figure-generation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "figure-generation", 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 lingzhi227/agent-research-skills figure-generationInstalls 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 lingzhi227/agent-research-skills --skill figure-generation -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/lingzhi227/agent-research-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/figure-generation .github/skills/figure-generation && 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 "figure-generation" agent skill from https://github.com/lingzhi227/agent-research-skills/tree/main/skills/figure-generation into .github/skills/figure-generation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "figure-generation", 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 lingzhi227/agent-research-skills --skill figure-generation -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install lingzhi227/agent-research-skills figure-generation --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/lingzhi227/agent-research-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/figure-generation .opencode/skills/figure-generation && 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 "figure-generation" agent skill from https://github.com/lingzhi227/agent-research-skills/tree/main/skills/figure-generation into .opencode/skills/figure-generation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "figure-generation", 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
figure-generation- GitHub stars
- 390
- Token cost
- ~809 tokens
- SKILL.md length
- 269 words
- Files
- 3 (incl. scripts, references)
- Skills in repo
- 31
- Repo updated
- First seen
- Licence
- None found
At a glance
Generates publication-quality scientific figures with matplotlib or seaborn through query expansion, a run-and-retry coding loop and a visual check of the rendered PNG.
- Works in 3 steps: Query Expansion → Code Generation with Execution Loop (up… → Visual Refinement
- Producing bar charts, heatmaps or training curves for a paper
- SKILL.md covers Input, Scripts, Three-Phase Pipeline (from… and References, plus 3 more sections
- Runs Python scripts from its folder; calls python
What it does
This skill turns a figure description, and optionally a data file in CSV, JSON, NPY or PKL form or a results folder, into a research-paper figure. It works in three phases borrowed from MatPlotAgent: expand the request into step-by-step coding specs using the prompts in references/figure-prompts.md, generate a self-contained Python script and run it with up to four retries on errors or a missing PNG, then look at the rendered image and correct what is off. A helper, scripts/figure_template.py, offers starter templates for bar, training-curve, heatmap, ablation, line, scatter, radar, violin, tsne and attention figures.
Each run saves a PNG preview at 300 DPI and a vector PDF, together with LaTeX figure-include code. The visual pass checks that the figure type matches the request, that labels, titles and legends are right, that colors are consistent, and that text is readable at print size. The stated quality requirements are at least 300 DPI or vector output, a colorblind-friendly palette, text of at least 8pt, consistent styling across a paper's figures, and captions written in LaTeX instead of matplotlib's default title.
When your agent uses it
- Producing bar charts, heatmaps or training curves for a paper
- Making ablation plots with consistent styling across figures
- Regenerating a figure until labels, legends and scales look right
- Exporting a vector PDF plus LaTeX include code
Example prompts
- “Plot the training and validation loss from results/run1.json as a training curve for the paper.”
- “Make an ablation bar chart from ablation.csv with a colorblind-friendly palette.”
- “Draw a heatmap of the attention weights saved in attn.npy and give me the LaTeX include snippet.”
Requirements
- Python with matplotlib or seaborn
Workflow steps
3 steps, taken from the step headings in SKILL.md.
- Query Expansion
- Code Generation with Execution Loop (up to 4 retries)
- Visual Refinement
What it can do on your machine
Read from SKILL.md and the folder at commit 9e6c085. 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
Ships 1 file in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
python
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
Scientific Figure Generation loads about 809 tokens when it runs, and up to ~1.9k if it reads all its reference files. Until then it costs about 87 tokens; SKILL.md has 269 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); the scripts in this folder are not scanned.
SKILL.md
Without a licence we can't republish the file, so here is its outline and opening line. It has 269 words (~809 tokens).
“Generate publication-quality figures for research papers.”
- name
- figure-generation
- argument-hint
- figure-description
Files
SKILL.md and 2 other files (scripts, references) in skills/figure-generation of lingzhi227/agent-research-skills.
- SKILL.md
- references/figure-prompts.md
- scripts/figure_template.py
Open the folder on GitHubat commit 9e6c085
Compare with similar skills
Scientific Figure Generation 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 |
|---|---|---|---|---|---|---|
| Scientific Figure Generation this skilllingzhi227/agent-research-skills | 390 | — | ~809 | Automated safety check: Pass | None | |
| Ieee Figure TableCloudWave818/ieee-skills | 359 | — | ~1k | Automated safety check: Pass | MIT | |
| Nature FigureCitrus-bit/Anaxa | 120 | 2 repos | ~2.7k | Automated safety check: Pass | MIT | |
| CJK Font Setup for Plotsxjtulyc/MedgeClaw | 617 | 1 repos | ~1.3k | Automated safety check: Pass | None | |
| Release Evidence WorkflowAli-Marandi/ClimateDataAnalyzer | 107 | — | ~1.6k | Automated safety check: Pass | MIT | |
| Scientific VisualizationOleafly/Oleafly | 212 | — | ~3.4k | Automated safety check: Notes | MIT |
Similar skills
Nature Figure
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CJK Font Setup for Plots
xjtulyc/MedgeClaw
Detects a usable Chinese, Japanese or Korean font and configures matplotlib so chart labels, titles and legends render instead of showing empty boxes.
Release Evidence Workflow
Ali-Marandi/ClimateDataAnalyzer
Build an auditable release-evidence workflow for a desktop or packaged application.
Scientific Visualization
Oleafly/Oleafly
Create and audit truthful, accessible, publication-ready scientific figures with Matplotlib, Seaborn, or Plotly.
Intelligrapher
MrLee2R/Intelligrapher
科研绘图智能助手。当用户需要科研绘图、数据可视化、配色建议、期刊风格调整、生成 matplotlib 或 seaborn 绘图代码、或询问某专业领域图表规范时触发。支持多领域与顶刊审美，输出可直接运行的 Python 脚本。
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Related
Works with
Categories
Questions about Scientific Figure Generation
What does Scientific Figure Generation do?
Generates publication-quality scientific figures with matplotlib or seaborn through query expansion, a run-and-retry coding loop and a visual check of the rendered PNG. This skill turns a figure description, and optionally a data file in CSV, JSON, NPY or PKL form or a results folder, into a research-paper figure.md, generate a self-contained Python script and run it with up to four retries on errors or a missing PNG, then look at the rendered image and correct what is off.
When should I use Scientific Figure Generation?
Scientific Figure Generation fits situations like: producing bar charts, heatmaps or training curves for a paper; making ablation plots with consistent styling across figures; regenerating a figure until labels, legends and scales look right; exporting a vector PDF plus LaTeX include code.
How do I install Scientific Figure Generation in Claude Code?
Run `npx skills add lingzhi227/agent-research-skills --skill figure-generation -a claude-code`. Or copy the skill folder (skills/figure-generation in lingzhi227/agent-research-skills) into .claude/skills/figure-generation in your project. Claude Code loads it when a task matches its description.
How do I install Scientific Figure Generation in Codex?
Run `npx skills add lingzhi227/agent-research-skills --skill figure-generation -a codex`. Or copy the skill folder (skills/figure-generation in lingzhi227/agent-research-skills) into .agents/skills/figure-generation in your project. Codex loads it when a task matches its description.
Can I use Scientific Figure Generation 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 lingzhi227/agent-research-skills --skill figure-generation -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/figure-generation, .gemini/skills/figure-generation, .github/skills/figure-generation and .opencode/skills/figure-generation in your project.
What does Scientific Figure Generation need to run?
Going by SKILL.md and its folder, Scientific Figure Generation needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python with matplotlib or seaborn.
Does Scientific Figure Generation 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 Scientific Figure Generation 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Scientific Figure Generation use?
No licence was found for Scientific Figure Generation or its repository. Without one, default copyright applies: ask the author before reusing or redistributing it.
How many tokens does Scientific Figure Generation use?
About 809 tokens (SKILL.md is roughly 3.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.1k tokens, read only when the agent opens those files.
What are the alternatives to Scientific Figure Generation?
Skills that share tags, products or a category with Scientific Figure Generation: Ieee Figure Table (CloudWave818/ieee-skills, 359 stars), Nature Figure (Citrus-bit/Anaxa, 120 stars), CJK Font Setup for Plots (xjtulyc/MedgeClaw, 617 stars) and Release Evidence Workflow (Ali-Marandi/ClimateDataAnalyzer, 107 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Scientific Figure Generation?
lingzhi227 (a GitHub user) maintains it in lingzhi227/agent-research-skills, which has 390 GitHub stars. The repository holds 31 skills in this directory. The repository was last updated on February 27, 2026.
Source: lingzhi227/agent-research-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.