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 nature-polishinggit 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/nature-polishing)<a href="https://agentmods.dev/skills/researai/deepscientist/nature-polishing"><img src="https://agentmods.dev/badge/skills/researai/deepscientist/nature-polishing/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/nature-polishing"><img src="https://agentmods.dev/badge/skills/researai/deepscientist/nature-polishing.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 | $0.02750 |
| Opus 5 | $0.00040 | $0.01375 |
| Sonnet 5 | $0.00016 | $0.00550 |
| Haiku 4.5 | $0.00008 | $0.00275 |
Grade A, and why
nature-polishing 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 11d 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
83% identical to nature-polishing — 31 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 — 386 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Nature-Style Academic Polishing
This companion skill is adapted from Yuan1z0825/nature-skills/tree/main/nature-polishing.
See UPSTREAM_LICENSE.txt for the upstream MIT license.
DeepScientist integration
- Follow the shared interaction contract injected by the system prompt.
- Use this inside
write,review, orrebuttalwhen the user asks for Nature-leaning English, Chinese-to-English manuscript polishing, section restructuring, or publication-quality academic prose. - Apply it after the evidence and claim boundary are clear. Do not use style polishing to hide missing support, overstate novelty, or make unsupported claims sound stronger.
- Keep DeepScientist manuscript hygiene rules authoritative: no user/operator/agent provenance, route-control wording, prompt state, or local implementation shorthand in paper-facing prose.
Use this skill to improve scientific writing at two levels:
main strategy: paper architecture, section logic, reader workflow, evidence thresholds, and ethicsreference support: reusable phrase families, move patterns, transitions, and style checks
The main strategy should come from the course notes in Chapter1-Week1-7. The reference wording layer should come from Academic Phrasebank.
Default stance
- Language serves argument. Do not polish sentences while leaving the reasoning broken.
- Write with empathy for the reader: relevance first, then novelty, then trust, then reuse, then meaning.
- There should be no mystery for the writer, but there may be one for the reader.
- Do not invent data, references, mechanisms, or novelty claims.
- Do not let AI draft the paper's core scientific argument from scratch.
- If the draft is Chinese or structurally rough, reconstruct the logic first and the prose second.
When to open extra files
These files are reference support. Use them after the section's rhetorical job is clear.
| File | Open when |
|---|---|
| references/section-moves.md | You need section-specific move orders or phrase patterns derived from Academic Phrasebank |
| references/phrasebank-playbook.md | You need hedging, transition, evidence, limitation, or future-work phrase families |
| references/style-guardrails.md | You need academic-style checks, paragraph/sentence checks, article use, register, or mechanics |
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.
- 11d ago First seen · 386 lines · 80 tokens per session scan A e232fa09c1a0
nature-polishing is a skill published in the GitHub repository ResearAI/DeepScientist (3,323 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 80 tokens to every session and 2,750 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 83% identical to nature-polishing, differing in 31 lines, and is treated as a copy.
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