Academic Figure Architecture Extractor
SkillDev toolsExtract semantic structure and transferable style grammar from academic figures, PDFs, and paper or figure URLs for analysis, redraws, or reference-conditioned generation. Do not use it for paper-text-only figure planning.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Academic Figure Architecture Extractor skill
What this skill tells your AI
The instructions your AI receives, as published by azhi-ss/academic-figure-skills in academic-figure-architecture-extractor/SKILL.md and read by ahel’s review.
Turn supplied figures into grounded structure and reference-style evidence. Keep scientific content separate from transferable visual grammar.
Load only when relevant:
- missing evidence →
references/missing-info-policy.md - local PDF helper →
scripts/extract_pdf_figures.py
Scope and inputs
Accept one or more local images, PDFs, public paper/figure URLs, or an existing render that needs revision. Prefer the original figure image over a screenshot when both exist. PDF extraction finds embedded images or rasterized pages; it is not an architecture detector, and figure classification remains evidence-based judgment.
For an article URL, inspect the page with an available web or browser tool, locate the requested figure and caption, and resolve its direct image or PDF source. Do not classify a paper URL as a repository. If a renderer will need the reference, retain or download it to an absolute local path without overwriting user files.
Obtain candidates
- Local image: inspect it with an available image-viewing tool at original detail.
- Remote figure: open it, preserve its source URL and caption, then inspect the localized image when possible.
- PDF: use a PDF-capable reader for pages and captions. To extract candidates, run the bundled helper from the skill repository when available:
python3 academic-figure-architecture-extractor/scripts/extract_pdf_figures.py \
/absolute/path/to/paper.pdf -o /absolute/path/to/extraction-directory
Useful optional flags are --backend auto|pdfimages|pymupdf, --pages 1-3|all,
--dpi 150, --min-side 300, and --min-pixels 90000. Read the generated
extract-report.json. If extraction tools are unavailable, use directly viewable
pages or ask for an exported figure; never invent a local path.
Record for every candidate: source URL/path, page or figure number, caption, pixel size, local absolute path when available, and keep/drop/uncertain with a reason.
Analyze semantic structure
For each kept figure, identify only what the image and caption support:
- components and their core/auxiliary roles;
- groups, hierarchy, reading direction, and dominant focal point;
- directed edges, branches, loops, annotations, and legend semantics;
- figure type and uncertain or illegible content.
Do not import the reference's labels, claims, metrics, or topology into a new method figure. Those are reusable only when the user explicitly requests a faithful redraw.
Extract the style grammar
Describe observable design decisions rather than reducing the figure to a palette name. Capture:
composition: storyboard|pipeline|loop|modular collage|nested mechanism|other
regions: panel geometry, grouping, asymmetry, whitespace and density
marks: vector, hand-drawn, editorial illustration, geometric, line-art, mixed
strokes: weight, curvature, joins, arrow and connector language
fills: flat/tinted/wash/white, border treatment, shadow and texture
color_roles: background, regions, primary structure, accents, exceptions
typography: family character, hierarchy, placement and approximate density
motifs: agents, scientific objects, tokens, icons, mini-plots, callouts
emphasis: focal scale, contrast, saturation and annotation strategy
avoid: visual traits absent from or conflicting with the reference
Do not force classic versus pastel, Nature Blue, white-fill boxes, or a venue
stereotype. A reference may define a third style family such as a hand-drawn
editorial scientific infographic. Treat exact hex values as observations, not as a
substitute for composition and hierarchy.
ReferenceAnalysis v1 handoff
Emit one JSON-compatible object per kept figure:
schema: academic-figure/ReferenceAnalysis@1
reference_id
source: {url_or_absolute_path, local_absolute_path, page_or_figure, caption, size}
semantic_structure: {components[], groups[], edges[], reading_order, uncertainties[]}
style_grammar: {composition, regions, marks, strokes, fills, color_roles,
typography, motifs, emphasis, avoid[]}
transfer_policy: {reuse[], do_not_copy[]}
confidence: high|partial|sparse
Downstream FigurePlan v1 carries reference_id and style_grammar; FigureSpec v1
carries the reference's absolute local path whenever it can be materialized. If
the asset exists only in the current conversation, it may use the workflow's
transient recent-conversation descriptor for the immediate render, but should be
materialized before a reproducible rerun. A capable backend conditions on the
image itself. A later RenderAudit v1 compares observable style fidelity without
requiring content imitation.
Stop after the inventory if that is all the user requested. Otherwise stop when ReferenceAnalysis v1 is complete or when a missing source image blocks honest analysis.
Signals
- GitHub stars
- 106
- Forks
- 10
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
academic-figure-architecture-extractor- Source
- github.com/azhi-ss/academic-figure-skills