academic-plotting agent skill by Orchestra-Research
Generates publication-quality figures for ML papers, including architecture diagrams via Gemini and data-driven charts via matplotlib or seaborn, from research context.
At a glance
| Publisher | Orchestra-Research |
|---|---|
| Repository | Orchestra-Research/AI-Research-SKILLs (81 listed skills) |
| Category | Science and Research |
| License | MIT |
| Last commit | June 15, 2026 (repository) |
| SKILL.md | 469 lines, 2,766 words |
| Bundled files | 4 files, including references |
| Quality score | 77/100 · C Passes all seven graded checks |
| Security scan | Not scanned |
| README badge | Get the listing badge and raise the score |
Before you install
Read from the skill's files at the directory's October 19, 2026 snapshot: what ships with it, what its code reads, and the terms it is published under.
- Bundled scripts: none.
- Credential names SKILL.md mentions:
GEMINI_API_KEY. - License: MIT, an open-source or open-content license.
Install academic-plotting
The skills CLI works with Claude Code, Codex, Cursor and other agents; the other routes copy the folder by hand.
npx skills add https://github.com/Orchestra-Research/AI-Research-SKILLs/tree/main/20-ml-paper-writing/academic-plottingtmp="$(mktemp -d)"
git clone --depth 1 https://github.com/Orchestra-Research/AI-Research-SKILLs.git "$tmp/repo"
mkdir -p .claude/skills
cp -R "$tmp/repo/"20-ml-paper-writing/academic-plotting .claude/skills/
rm -rf "$tmp"python3 ~/.codex/skills/.system/skill-installer/scripts/install-skill-from-github.py \
--repo Orchestra-Research/AI-Research-SKILLs \
--path 20-ml-paper-writing/academic-plottingOrchestra-Research/AI-Research-SKILLs is third-party code. Read SKILL.md and any bundled scripts before you install it.
How the author describes it
Generates publication-quality figures for ML papers from research context. Given a paper section or description, extracts system components and relationships to generate architecture diagrams via Gemini. Given experiment results or data, auto-selects chart type and generates data-driven figures via matplotlib/seaborn. Use when creating any figure for a conference paper.
From the description field of SKILL.md. Agents read this line to decide when to load the skill.
Sections in SKILL.md
- When to Use Which Workflow
- Step 0: Context Analysis & Extraction
- Extraction Workflow
- Auto-Detection Examples
- Workflow 1: Architecture & System Diagrams (AI Image Generation)
- Visual Styles
- Curated Color Palettes
- Checklist
- Prompt Structure (6 Sections)
- Generation Script Template
- Key Rules
- Workflow 2: Data-Driven Charts (matplotlib/seaborn)
- Checklist
- Chart Type Decision Guide
- Publication Styling Template
- Common Chart Patterns
Files in the skill folder
SKILL.mdreferences/data-visualization.mdreferences/diagram-generation.mdreferences/style-guide.md
Suede Skill Check: 77/100 · C
Report snapshot · · graded-v2
The rubric totals 100 points; published scores are capped at 99. Security scan: not scanned.
Source revision: 773a52944ba4. Report version 49c212b331ad. Badge URLs follow the latest listing; save the report to keep this version.
Download report · Request a fresh review
What to review next
- Recent maintenance: 3 of 9 points. 9 for a repository commit within 30 days of the snapshot; 6 within 90; 3 within 180; 1 within 365.
- Boundary clause: 0 of 4 points. 4 when the description says when not to use the skill (“Not for …”, “Do not use …”, “Use … instead”).
- Example request: 0 of 3 points. 3 when the description quotes an example request (3–60 characters in quotation marks).
Add declarations and bundled files when they describe the skill’s actual needs. Update the source, then request a fresh review with the changed commit or PR.
academic-plotting passes the required frontmatter check and all seven graded checks, which cover the SKILL.md format, a declared license and a commit in the last year. Those checks earn 56 of the score’s points; the rest come from description quality, instruction depth, bundled files, maintenance and curated-list citations. How the score works.
See the checks and points
| Check | Result |
|---|---|
| Frontmatter parses and declares a name and a description | Pass |
| Name uses lowercase letters, digits and hyphens, 64 characters or fewer | Pass |
| Name matches the skill's folder name | Pass |
| Description is between 50 and 1,024 characters | Pass |
| Description says when an agent should use the skill | Pass |
| SKILL.md body is 500 lines or fewer | Pass |
| A license is declared in the frontmatter or the repository | Pass |
| Repository has a commit in the last 12 months | Pass |
| Score component | Points |
|---|---|
| Structural checks | 56 of 56 |
| Description length | 5 of 5 |
| Boundary clause | 0 of 4 |
| Example request | 0 of 3 |
| Instruction depth | 7 of 7 |
| Reference files | 3 of 3 |
| Bundled scripts | 0 of 2 |
| Recent maintenance | 3 of 9 |
| Curated-list citations | 3 of 7 |
| Tool permissions declared | 0 of 2 |
| Compatibility declared | 0 of 2 |
Show the listing and raise the score
academic-plotting is listed with 77/100 · C. This badge links to its Suede listing. Skills scoring 80–99 add a numeric and a letter quality shield; the largest open points for academic-plotting are recent maintenance (6), boundary clause (4) and example request (3). Send your repository and the points you want to raise, then request a fresh review after updating the skill.
[](https://skills.suedeai.ai/directory/orchestra-research/ai-research-skills/academic-plotting/)<a href="https://skills.suedeai.ai/directory/orchestra-research/ai-research-skills/academic-plotting/"><img src="https://skills.suedeai.ai/directory/badge.svg" alt="Suede Skills Directory: listed" height="20"></a>Where this skill is cited
Orchestra-Research/AI-Research-SKILLs appears in 2 curated lists: VoltAgent/awesome-agent-skills, skillmatic-ai/awesome-agent-skills.