Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add neuromechanist/research-skills --skill ai-full-figuregit clone --depth 1 https://github.com/neuromechanist/research-skillsWrote 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/neuromechanist/research-skills/ai-full-figure)<a href="https://agentmods.dev/skills/neuromechanist/research-skills/ai-full-figure"><img src="https://agentmods.dev/badge/skills/neuromechanist/research-skills/ai-full-figure/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/neuromechanist/research-skills/ai-full-figure"><img src="https://agentmods.dev/badge/skills/neuromechanist/research-skills/ai-full-figure.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00166 | $0.01647 |
| Opus 5 | $0.00083 | $0.00823 |
| Sonnet 5 | $0.00033 | $0.00329 |
| Haiku 4.5 | $0.00017 | $0.00165 |
Grade A, and why
ai-full-figure 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 12d 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.
How it starts
The opening of the file, as written. The whole thing — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Full Figure
Generate a pictorial substrate via AI (Codex CLI or OpenAI Images API) and overlay labels, arrows, and scale bars programmatically. The output is an SVG that embeds the raster substrate and lets the [[scientific-figure]] composer place it as a panel.
When to use this skill
Reach for ai-full-figure when the figure's picture is the point:
- A brain rendering for a methods overview slide
- A microscope or apparatus illustration for a poster
- An anatomical scene as the background of a graphical abstract
- Any "what does this setup look like" pictorial
Reach for a different skill when the figure is information-dense:
| Figure type | Skill |
|---|---|
| Data plot (matplotlib, seaborn, plotly) | [[plot-styling]] for the plot, then [[scientific-figure]] to compose |
| Schematic with boxes / arrows / process flow | [[svg-primitives]] (programmatic) or [[svg-figure]] (hand-authored conventions) |
| Flat scientific icon as part of a figure | [[transparent-icons]] |
| Multi-panel journal figure | [[scientific-figure]] as the composer |
Hard ceiling on AI generation
gpt-image-2 and equivalent models cannot reliably render:
- Data plots with axis numerals (axes hallucinate, tick labels are nonsense)
- Equations (LaTeX or Greek-letter math)
- Multi-arrow flowcharts (arrow direction inconsistent, arrows cross wrong)
- Long labels in specific positions ("> 5 labeled elements" is a useful threshold)
- Anything that needs to be read precisely — labels >1–2 words drift
The right pattern when those are needed: substrate-only generation, programmatic overlay.
- Prompt the model for the pictorial scene with no text, no labels, no arrows.
- Compose labels, arrows, scale bars, and panel letters as a separate SVG layer.
- Ship the combined SVG.
If the user is asking for a figure that violates the hard ceiling, route to [[svg-figure]] or [[scientific-figure]] and explain why. AI generation for embedded text remains unreliable as of 2026.
What ships with it
6 files 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.
- 12d ago First seen · 128 lines · 166 tokens per session scan A 32261a2c22c9
ai-full-figure is a skill published in the GitHub repository neuromechanist/research-skills (45 stars, last pushed 9d ago), licensed BSD-3-Clause. It adds 166 tokens to every session and 1,647 once invoked, about $0.0008 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
godot-optimization
Use when optimizing Godot games — profiler, draw calls, physics tuning, memory management, and common bottlenecks.
food-analyzer
Analyze food photos, nutrition labels, and ingredient lists. Trigger on food images, nutrition label scans, macro questions, glycemic questions, medication interaction checks, and similar food-analysis requests.
astrophotography-processing
Router for astrophotography processing, troubleshooting, and safe workflow guidance across deep-sky, narrowband, planetary/lunar/solar, Milky Way landscape, comet, and mosaic data.
scientific-slides
Build slide decks and presentations for research talks. Use this for making PowerPoint slides, conference presentations, seminar talks, research presentations, thesis defense slides, or any scientific talk. Provides slide structure, design templates, timing guidance, and visual validation. Works with PowerPoint and…
LQF_Machine_Learning_Expert_Guide
LQF Machine Learning Expert Guide - Routed skill for ML/Statistical Modeling with Critical Discussion Mode. Triggers on: machine learning, modeling, prediction, training, classification, regression, clustering, deep learning, neural network, model evaluation, feature engineering, hyperparameter tuning, overfitting…
imaging-data-commons
Query and download public cancer imaging data from NCI Imaging Data Commons using idc-index. Use for accessing large-scale radiology (CT, MR, PET) and pathology datasets for AI training or research. No authentication required. Query by metadata, visualize in browser, check licenses.