Individual skill
figure-spec
Generate deterministic publication-quality architecture, workflow, and pipeline diagrams from structured JSON (FigureSpec) into editable SVG. Use when user says "架构图", "workflow 图", "pipeline 图", "确定性矢量图", "figure spec", "draw architecture", or needs precise, editable, publication-ready vector diagrams. Preferred over AI illustration for formal architecture/workflow figures.
skills/skills-codex/figure-spec/SKILL.md
Source commit 2901234ad2954cd2388ced8d3aed2ed9de42803a
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- Last checked
- Nov 9, 2026
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- Repository last updated
- Nov 8, 2026
- License
- MIT
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- ai-research Repository topic
- autonomous-agent Repository topic
- claude-code Repository topic
- codex Repository topic
- mcp Repository topic
- ml-research Repository topic
- paper-review Repository topic
- research-automation Repository topic
- ai-tools Repository topic
- claude Repository topic
- engineering Derived category
- operations Derived category
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# FigureSpec: Deterministic JSON → SVG Figure Generation
> **Before each reviewer slot**, follow [Selectable Reviewers](../shared-references/reviewer-backends.md):
> resolve invocation → `.aris/reviewer.json` → Codex default (fresh native reviewer)
> with `reviewer_route.py` through the canonical helper resolver, preserving this
> slot's tier, fresh contexts, source/image inputs and deterministic gates.
> Codex examples/pins below apply only to `backend=codex`; other routes use their
> own first-call/reply contract. Save the route and actual returned identity;
> unavailable selections are `REVIEW_UNAVAILABLE`. Classify acceptance from actual
> families/completion/scope. Forward invocation reviewer/model/effort overrides
> to reviewer-bearing children. Generation workers are unchanged.
Generate publication-quality **architecture diagrams**, **workflow pipelines**, **audit cascades**, and **system topology** figures as editable SVG vector graphics using a deterministic JSON → SVG renderer.