AutoResearchClaw is a system that turns a research idea into a scientific paper through autonomous and collaborative AI research workflows. It is for researchers who want agents to investigate questions, run experiments, and produce papers, with optional human guidance. Catalogue skills and agents provide parts of its research workflow.
Borrowing it
Nothing to install: this file belongs to aiming-lab/AutoResearchClaw. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/aiming-lab/AutoResearchClaw/main/.claude/skills/scientific-writing/SKILL.mdgit clone --depth 1 https://github.com/aiming-lab/AutoResearchClawWrote 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/aiming-lab/autoresearchclaw/scientific-writing)<a href="https://agentmods.dev/skills/aiming-lab/autoresearchclaw/scientific-writing"><img src="https://agentmods.dev/badge/skills/aiming-lab/autoresearchclaw/scientific-writing/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/aiming-lab/autoresearchclaw/scientific-writing"><img src="https://agentmods.dev/badge/skills/aiming-lab/autoresearchclaw/scientific-writing.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 | $0.00028 | $0.00626 |
| Opus 5 | $0.00014 | $0.00313 |
| Sonnet 5 | $0.00006 | $0.00125 |
| Haiku 4.5 | $0.00003 | $0.00063 |
Grade A, and why
scientific-writing 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.
How it starts
The opening of the file, as written. The whole thing — 57 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Scientific Writing Best Practice
IMRAD Structure
- Abstract: State objective, methods, key results, and conclusion in 150-300 words
- Introduction: Move from broad context to specific gap to your contribution (funnel structure)
- Methods: Sufficient detail for replication; use past tense, passive voice
- Results: Present findings without interpretation; pair text with figures/tables
- Discussion: Interpret results, compare with literature, acknowledge limitations, state implications
Paragraph-Level Guidance
- Each paragraph should convey ONE main idea
- Open with a topic sentence; close with a transition to the next paragraph
- Write in full flowing prose — never submit bullet points as final manuscript text
- Use active voice for clarity: "We measured..." not "Measurements were taken..."
- Vary sentence length; aim for average 15-25 words per sentence
Citation Best Practices
- Cite primary sources over reviews when making specific claims
- Use citation styles consistently (APA, Vancouver, IEEE) per target journal
- Every factual claim needs a citation unless it is common knowledge in the field
- Avoid citation strings of 5+ references — select the most relevant 2-3
- Self-citations should be limited to genuinely relevant prior work
Common Writing Pitfalls
- Avoid hedge-stacking: "It might possibly suggest..." — choose one hedge
- Do not start sentences with "It is well known that" — cite or remove
- Distinguish "significant" (statistical) from "substantial" (practical)
- Ensure figures/tables are referenced in text BEFORE they appear
- Keep abbreviations to a minimum; define each on first use
Reporting Guidelines
- Randomized trials: follow CONSORT checklist
- Observational studies: follow STROBE checklist
- Systematic reviews: follow PRISMA checklist
- Diagnostic accuracy: follow STARD checklist
- Always check target journal's author guidelines for specific requirements
Revision Checklist
- Verify all figures/tables are cited in text and numbered sequentially
- Confirm reference list matches in-text citations exactly
- Check that abstract accurately reflects the final manuscript content
- Ensure methods section enables independent replication
- Read aloud to catch awkward phrasing and run-on sentences
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 · 57 lines · 28 tokens per session scan A d744442c5165
scientific-writing is a skill published in the GitHub repository aiming-lab/AutoResearchClaw (14,389 stars, last pushed 22d ago), licensed MIT. It adds 28 tokens to every session and 626 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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