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/KhaledSaeed18/dotclaudenpx agentmods add skills/khaledsaeed18/dotclaude/research-figuresWrote 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/khaledsaeed18/dotclaude/research-figures)<a href="https://agentmods.dev/skills/khaledsaeed18/dotclaude/research-figures"><img src="https://agentmods.dev/badge/skills/khaledsaeed18/dotclaude/research-figures/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/khaledsaeed18/dotclaude/research-figures"><img src="https://agentmods.dev/badge/skills/khaledsaeed18/dotclaude/research-figures.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 | $0.00096 | $0.01568 |
| Opus 5.5 | $0.00038 | $0.00627 |
| Sonnet 5.5 | $0.00019 | $0.00314 |
| Haiku 4.5 | $0.00010 | $0.00157 |
Grade A, and why
research-figures 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 25d 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 — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.
A figure earns its place by making one claim visible faster than the table does. Design from the claim, not from the data: decide what the reader must see, then choose the encoding that shows it.
Rules that apply to every figure
- One claim per figure. If the caption needs "and also", split it.
- Vector output (
.pdffor LaTeX,.svgor 300-dpi.pngfor Word) at the final printed size, so fonts are not scaled. Text width in a typical thesis is about 6 inches (15 cm); setfigsizeaccordingly and never rescale in the document. - Fonts match the document: same family (or the closest available) and a size between the caption size and the body size (9 to 11 pt at print size). Set once in the style file.
- Colour-blind-safe palette (Okabe-Ito or viridis for sequential data). Never encode a difference by colour alone: vary marker or line style too, and check the figure in greyscale.
- Show variance: error bars, confidence bands, or individual points. State in the caption what the bar is (SD, SEM, 95% CI) and n.
- Direct labels at line ends beat legends when there are fewer than six series.
- Axes start at zero for bar charts; for line charts, start where the data live and say so. Label with quantity and unit. Log scale when the data span orders of magnitude, stated in the label.
- No chartjunk: no 3D, no gradients, no gridlines heavier than the data, no titles inside the figure (the caption is the title).
- Consistency: the same variable has the same colour in every figure of the thesis. Keep a
colorsdict in the style module. - Reproducible: every figure comes from a script in
figures/src/that reads the data file and writes the output. No hand-edited figures.
Setup
figures/src/style.py:
import matplotlib as mpl
import matplotlib.pyplot as plt
OKABE_ITO = ["#0072B2", "#E69F00", "#009E73", "#D55E00", "#CC79A7", "#56B4E9", "#F0E442", "#000000"]
COLORS = {"baseline": OKABE_ITO[0], "ours": OKABE_ITO[3]} # one entry per named series, thesis-wide
def use_thesis_style(text_width_in=6.0, ratio=0.6):
mpl.rcParams.update({
"figure.figsize": (text_width_in, text_width_in * ratio),
"font.family": "serif", "font.size": 10,
"axes.labelsize": 10, "axes.titlesize": 10,
"xtick.labelsize": 9, "ytick.labelsize": 9, "legend.fontsize": 9,
"axes.prop_cycle": mpl.cycler(color=OKABE_ITO),
"axes.spines.top": False, "axes.spines.right": False,
"axes.grid": True, "grid.alpha": 0.3, "grid.linewidth": 0.5,
"lines.linewidth": 1.5, "lines.markersize": 4,
"errorbar.capsize": 2,
"savefig.bbox": "tight", "savefig.pad_inches": 0.02,
"pdf.fonttype": 42, "ps.fonttype": 42, # embed TrueType, editable text
"text.usetex": False, # True if the LaTeX toolchain is present
})
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.
- 25d ago First seen · 94 lines · 96 tokens per session scan A 0f192df7e6ac
research-figures is a skill published in the GitHub repository KhaledSaeed18/dotclaude (5 stars, last pushed 2d ago), licensed MIT. It adds 96 tokens to every session and 1,568 once invoked, about $0.0004 per session on Opus 5.5. 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 2026-09-22.
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