Academic figure workflow

Skill Azhi-ss/academic-figure-skills/academic-figure-workflow

AI skills for academic paper figures: repo analysis, figure planning, colorblind palettes, JSON figure specs. Install: npx skills add Azhi-ss/academic-figure-skills

Install

npx -y skills add Azhi-ss/academic-figure-skills --skill academic-figure-workflow

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

What its author says it does

Copied from the file, not written here

End-to-end academic figure workflow router — from repo or paper to figure prompt via the minimum sibling skills. Use when the user wants a full pipeline, is unsure which academic-figure skill to start with, or says 完整论文配图工作流 / from paper to figure prompt.

SKILL.md

3.2 KB, as published. Nobody here has run it

Academic Figure Workflow Orchestrator

Pack entrypoint. Detect stage, load only needed sibling skills, carry compact handoffs.

Shared refs:

palettes → ../docs/palettes.md
missing info → ../docs/missing-info-policy.md

Sibling routing

Read a sibling file only when that stage runs:

skill	when
`../academic-repo-analyzer/SKILL.md`	repository / codebase understanding
`../academic-figure-paper-analyzer/SKILL.md`	paper/section → figure plan
`../academic-figure-architecture-extractor/SKILL.md`	PDF/images → architecture analysis
`../academic-figure-color-expert/SKILL.md`	palette decision
`../academic-figure-prompt/SKILL.md`	classic JSON figure spec
`../academic-figure-prompt-pastel/SKILL.md`	pastel / ICLR airy style

Stage detection

Repo-first — codebase before figures
Paper-first — paper/PDF/outline → plan
Architecture-extraction-first — extract/analyze existing diagrams
Prompt-first — figure already known
Color-first — palette only

Infer from artifacts; ask only for blockers.

Default paths (lightest valid)

Repo-first → repo-analyzer → (paper-analyzer if planning) → (color if needed) → prompt
Paper-first → paper-analyzer → (color if needed) → prompt
Architecture-first → architecture-extractor → (paper-analyzer if planning) → (color if needed) → prompt
Prompt-first → style choice → min missing details → prompt
Color-first → color-expert → optional prompt

Never force the full chain for a single-stage ask.

Defaults

Style family then palette: follow docs/palettes.md (classic JSON vs pastel airy; ≥4 modules → Nature Blue; else Okabe-Ito). Always state the branch.
ICLR / NeurIPS / ICML airy / pastel / “现代一点” language → prompt-pastel + P1–P3
Otherwise → prompt JSON + classic 12 presets
Repo + paper both present → plan from paper; repo fills technical gaps
When user only asks “用什么配色/风格”, load color-expert and the Scene → palette section of docs/palettes.md

Handoffs (carry forward, don't re-narrate)

Quick Understanding Doc — task, stack, modules, flows, figure-worthy innovations
Figure Plan — count, types, section map, priorities, visual musts
Palette Decision — name, hex, reason, accessibility
Prompt Package / Figure Spec — final deliverable + assumptions

Output shape

Current stage
Next action
Result or required clarification
Handoff artifact or final prompt

Stop

requested stage deliverable is done
next step blocked on missing source material
user wants evaluation, not generation

Do not auto-advance downstream unless the user asked end-to-end or clearly implied it.