Academic figure prompt
AI skills for academic paper figures: repo analysis, figure planning, colorblind palettes, JSON figure specs. Install: npx skills add Azhi-ss/academic-figure-skills
npx -y skills add Azhi-ss/academic-figure-skills --skill academic-figure-promptAssembled 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
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JSON figure spec for academic diagrams — exact_text layout control for framework, architecture, module, and comparison figures. Use when the user wants paper figure prompts, 架构图/框架图 specs, or academic-figure JSON (text prompts only as simple fallback).
SKILL.md
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Academic Figure Prompt
Default deliverable: a JSON figure spec (exact_* text locks + layout blocks + rendering rules). Text prompts only for simple charts or explicit user request.
Schema and examples: → json-schema.md
Palettes: → ../docs/palettes.md
Missing info: → ../docs/missing-info-policy.md
Text Budget (leading rule)
On-figure text is short labels and structure. Formulas, params, and long prose go to Figure Caption.
| element | limit |
|---|---|
| module title | ≤ 5 words |
| subcomponent | ≤ 3 words |
| pipeline step | ≤ 2 words primary + ≤ 2 secondary |
| formula on figure | ≤ 1 line core only |
| arrow label | ≤ 3 words |
Label hierarchy: Primary (must read at a glance) → Secondary (drop first under space pressure) → Caption (never on figure).
Input Contract
- Prefer: figure type, paper/section content, modules, labels, formulas, dims, Palette Decision, reference image
- Minimum: figure type + subject/method overview
- Missing: skeleton spec with placeholders; mark 推断 / 待确认
Output Contract — Figure Spec Package
- Chinese figure name + type
- JSON spec (default) or text prompt (fallback)
- palette name + hex used
- caption reserve list
- completeness block (see missing-info policy)
Steps
Step 1: Ground content
Read available paper/section material. Extract modules, dataflow, symbols, dims.
Done when: every claimed module has a source span or is marked placeholder.
Step 2: Reference image (if any)
Extract palette, layout flow, box style, annotation density, special links.
Done when: reference constraints are listed or “no reference” is explicit.
Step 3: Palette
Do not maintain a private palette table. This skill is classic family only (pastel → other skill).
- User-specified palette / hex → use it
- Else existing Palette Decision from color-expert → use it
- Else run
docs/palettes.mdScene → palette decision (hard constraints → type → venue → domain); if still empty, safe default (≥4 modules → Nature Blue; else Okabe-Ito) and say so - Load hex from
docs/palettes.md - If user signals airy/pastel, stop and route to
academic-figure-prompt-pastelinstead of forcing classic borders
Done when: palette name + hex are fixed, family is classic, and the decision branch is stated.
Step 4: Emit JSON spec
Load json-schema.md. Build layout_and_content_blocks with exact_* locks for every visible word. White fill + colored borders. Attach rendering rules and caption_note list.
Done when checklist passes:
- every on-figure string is in an
exact_*field - Text Budget respected
- white fill / colored borders only
- ≤ 3 chromatics from chosen palette
- caption reserve lists off-figure content
- no empty module shells
- weight status (frozen vs trainable) uses non-emoji pattern (dashed/solid borders, hatching, or pills)
- explicit negative instructions included:
NO emojis, NO lock/fire/lightning icons, NO 3D rendering
Step 5: Fallback text prompt (rare)
Only if ≤ 3 modules without branches, pure data chart, or user demands prose prompt. Use four-layer skeleton in json-schema.md (Global Context → Section/Column Encapsulation → Annotations & Links → Style Specifications with hex & negative constraints).
Stop
Stop when the Figure Spec Package for the requested figure(s) is delivered, or when figure type and subject are both missing (ask for those two only).