Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/AutoConference/AutoConference-skillnpx agentmods add skills/autoconference/autoconference-skill/figure-specWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/autoconference/autoconference-skill/figure-spec)<a href="https://agentmods.dev/skills/autoconference/autoconference-skill/figure-spec"><img src="https://agentmods.dev/badge/skills/autoconference/autoconference-skill/figure-spec/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/autoconference/autoconference-skill/figure-spec"><img src="https://agentmods.dev/badge/skills/autoconference/autoconference-skill/figure-spec.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00080 | $0.03000 |
| Opus 5.5 | $0.00032 | $0.01200 |
| Sonnet 5 | $0.00016 | $0.00600 |
| Haiku 4.5 | $0.00008 | $0.00300 |
Grade A, and why
figure-spec scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to figure-spec — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 263 lines — stays where its author put it; the contents beside it link to each section on GitHub.
FigureSpec: Deterministic JSON → SVG Figure Generation
Generate publication-quality architecture diagrams, workflow pipelines, audit cascades, and system topology figures as editable SVG vector graphics using a deterministic JSON → SVG renderer.
When to Use This Skill
Use figure-spec for:
- System architecture diagrams (layered, hub-and-spoke, multi-plane)
- Workflow / pipeline figures
- Audit cascade / flow-control diagrams
- Any structured diagram where node positions, connections, and groupings are semantically important
- Figures that need to be edited/tweaked later (SVG is plain text)
- Figures where determinism matters (same spec → same SVG)
Do NOT use for:
- Data plots (bar/line/scatter) — use
/paper-figure - Natural/qualitative illustrations — use
/paper-illustration - Quick state-machine / flowchart — use
/mermaid-diagram(lighter syntax)
Core Properties
- Deterministic: identical FigureSpec JSON always produces identical SVG output (for a fixed renderer version + fonts)
- Editable: SVG output is plain-text, can be post-edited by hand or programmatically
- Validated: renderer enforces schema, rejects malformed specs with clear error messages
- Shape-aware: edge clipping works correctly for rect/rounded/circle/ellipse/diamond
- CJK support: multi-line labels with proper Chinese character width estimation
- No external API: runs fully local, no network, no API keys
Tool Location
Phase 3.1 (Arch C) move: the canonical implementation now lives at
skills/figure-spec/scripts/figure_renderer.py (this SKILL's own
scripts/ subdirectory). A backwards-compatible shim at
tools/figure_renderer.py forwards to the canonical file via
os.execv, so existing users with .aris/tools/figure_renderer.py
or a manually copied tools/figure_renderer.py keep working
unchanged.
Resolve $FIGURE_RENDERER with the hybrid chain (layer 0 prefers the
self-contained location for the owning SKILL; layers 1-4 are the
shared-runtime chain documented in
shared-references/integration-contract.md §2,
Policy A — skill-local gate):
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 3d ago First seen · 263 lines · 80 tokens per session scan A 93c1018de5e7
figure-spec is a skill published in the GitHub repository AutoConference/AutoConference-skill (6 stars, last pushed yesterday), licensed Apache-2.0. It adds 80 tokens to every session and 3,000 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to figure-spec, differing in 2 lines, and is treated as a copy.
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