DeepScientist is a local research studio that manages the cycle from baseline experiments through research findings and paper-ready outputs. Researchers use it to organize autonomous scientific investigations, review progress, and take control when needed. The catalogue add-ons provide workflows and agent integrations for running research projects with it.
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 ResearAI/DeepScientist --skill figure-polishgit clone --depth 1 https://github.com/ResearAI/DeepScientistWrote 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/researai/deepscientist/figure-polish)<a href="https://agentmods.dev/skills/researai/deepscientist/figure-polish"><img src="https://agentmods.dev/badge/skills/researai/deepscientist/figure-polish/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/researai/deepscientist/figure-polish"><img src="https://agentmods.dev/badge/skills/researai/deepscientist/figure-polish.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 3 findings, 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 Agent Snooping · line 179 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
- medium Agent Snooping · line 180 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
- medium Agent Snooping · line 181 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 | $0.00037 | $0.01437 |
| Opus 5 | $0.00018 | $0.00718 |
| Sonnet 5 | $0.00007 | $0.00287 |
| Haiku 4.5 | $0.00004 | $0.00144 |
Grade A, and why
figure-polish 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 9d 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 — 184 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Figure Polish
Use this skill when a figure matters beyond transient debugging.
This includes:
- a main-experiment summary image sent to a connector
- an aggregated analysis-campaign chart
- a paper-facing main figure
- an appendix / supplementary figure
- any figure that will be stored as a durable artifact or cited in writing
Do not use this skill for disposable debug plots unless the user explicitly asks for them to be polished.
Core principle
DeepScientist figures should feel academic, restrained, and clear.
The goal is not to make a plot “fancy”. The goal is to make the intended comparison obvious without visual clutter.
Use one dominant message per figure. If multiple unrelated claims are competing inside the same image, split the figure instead of cramming everything into one panel.
Surface classes
First classify the figure:
connector_milestone- quick summary image for QQ / chat / copilot milestone reporting
- usually
png - message-first and minimal
paper_main- core paper figure
- export
pdforsvgplus apngpreview - must remain readable after likely single-column or double-column placement
appendix- supplementary figure
- may contain slightly more detail, but still avoid dashboard clutter
internal_review- used for local diagnosis and internal comparison
- can be lighter-weight, but still should follow the same visual discipline if it may later be promoted
Style contract
Prefer the bundled Matplotlib style asset when plotting in Python:
assets/deepscientist-academic.mplstyle
If you need a custom script, start from that style instead of inventing a fresh bright theme.
Default visual rules:
- white or near-white background
- muted Morandi palette only
- no neon colors
- no rainbow / jet-like colormaps
- no heavy shadows, glossy gradients, or thick black borders
- top and right spines removed unless a special plot truly needs them
- light grid only when it helps reading values
- legend minimal; prefer direct labeling when it is clearer
- main method should be visually dominant
- baseline or comparison lines should be slightly more neutral than the main method
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.
- 9d ago First seen · 184 lines · 37 tokens per session scan A 1182e639908b
figure-polish is a skill published in the GitHub repository ResearAI/DeepScientist (3,319 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 37 tokens to every session and 1,437 once invoked, about $0.0002 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
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paper-poster-html
A workflow for building an academic conference poster as one HTML/CSS file and printing it to a PDF at an exact page size. It uses the paper’s real figures and checks layout details before review.
paperFig
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latex-posters
Use when creating or revising LaTeX research posters with beamerposter, tikzposter, or baposter, including poster layout, typography, color, print sizing, figure placement, QR codes, compilation, and print-ready PDF checks.
figure-composer
Compose a publication-grade multi-panel scientific figure from a claim, dataset, or draft result. Use when the task needs panel planning, consistent figure layout, figure review, or final figure assembly.
ccf-visual-composer
A visual design assistant for research papers, presentations, posters, and README graphics. It can lay out figures, tables, diagrams, icons, colors, and other visual elements, including editable SVG, PDF, and PPTX outputs.