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/causify-ai/helpersnpx agentmods add skills/causify-ai/helpers/figure.create_tikz_from_descriptionWrote 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/causify-ai/helpers/figure.create_tikz_from_description)<a href="https://agentmods.dev/skills/causify-ai/helpers/figure.create_tikz_from_description"><img src="https://agentmods.dev/badge/skills/causify-ai/helpers/figure.create_tikz_from_description.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 3 Skill selects an external model or provider that may use a different account or billing plan than the operator expects. Undisclosed model switches can cause unexpected cost or quota consumption.Fix: Remove the model/provider override or disclose it prominently and require explicit operator approval before invoking an external coding CLI or billed model.
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 | $0.00011 | $0.00658 |
| Opus 5 | $0.00005 | $0.00329 |
| Sonnet 5 | $0.00002 | $0.00132 |
| Haiku 4.5 | $0.00001 | $0.00066 |
Grade A, and why
figure.create_tikz_from_description 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 8d 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 — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Purpose
- Convert images or textual descriptions into publication-quality TikZ LaTeX code Generate a compilable LaTeX file, render it to PNG, and iteratively refine the output to match the input precisely
When to Use
Use this skill when you need to:
- Create publication-quality diagrams, plots, or visualizations
- Convert hand-drawn sketches or existing images into reproducible TikZ code
- Generate diagrams for inclusion in LaTeX documents
When NOT to Use
Do not use this skill for:
- Complex photographs requiring photorealistic rendering
- Plots from large datasets (use dedicated plotting libraries instead)
- Diagrams requiring advanced 3D visualization
Workflow
Step 1: Generate TikZ Code
Generate valid LaTeX code using the TikZ package. Wrap the code in a complete minimal working example:
\documentclass{standalone}
\usepackage{tikz}
\begin{document}
\begin{tikzpicture}
...
\end{tikzpicture}
\end{document}
Preserve layout accurately
- If converting from an image
<image>, reproduce the layout precisely - Preserve proportions, relative positions, and symmetry
- Use coordinates and scaling where appropriate
- Approximate complex curves with TikZ paths when needed
Use appropriate TikZ features
- Nodes for labeled elements
draw,fill,shadefor shapes- Arrows and edge styles for connections
- Rounded corners for blocks:
[rounded corners=1cm] positioningandcalclibraries if helpful
Keep code clean and readable
- Use indentation for nested structures
- Define reusable styles for repeated elements
Handle ambiguity
- Make reasonable assumptions about unclear inputs
- Prioritize clarity and visual correctness over perfection
Step 2: Save the File
- Save the generated LaTeX code to
./tikz_figure.texin the current directory (not in.claude/). Output only valid TikZ code without markdown formatting or explanations
Step 3: Render to Image
- Generate a PNG image using the rendering script:
> ./helpers_root/dev_scripts_helpers/documentation/dockerized_tikz_to_bitmap.py \ -i tikz_figure.tex \ -o output.png
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.
- 8d ago First seen · 96 lines · 11 tokens per session scan A 9bcb4d42c0c0
figure.create_tikz_from_description is a skill published in the GitHub repository causify-ai/helpers (145 stars, last pushed yesterday), licensed Apache-2.0. It adds 11 tokens to every session and 658 once invoked, about $0.0001 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.
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