Scientific Agent Skills is a collection of reusable procedures that give AI agents capabilities for scientific research across areas such as biology, chemistry, medicine, and drug discovery. It is used by researchers and by people building AI scientist workflows with compatible coding agents. The catalogue contains many of the project's skills and supporting instructions.
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 K-Dense-AI/scientific-agent-skills --skill scientific-writinggit clone --depth 1 https://github.com/K-Dense-AI/scientific-agent-skillsWrote 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/k-dense-ai/scientific-agent-skills/scientific-writing)<a href="https://agentmods.dev/skills/k-dense-ai/scientific-agent-skills/scientific-writing"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agent-skills/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/k-dense-ai/scientific-agent-skills/scientific-writing"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agent-skills/scientific-writing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket warn
- Snyk warn
- 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 | $0.00060 | $0.03004 |
| Opus 5 | $0.00030 | $0.01502 |
| Sonnet 5 | $0.00012 | $0.00601 |
| Haiku 4.5 | $0.00006 | $0.00300 |
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 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.
Copies of this mod
2 near-identical copies found in the catalogue:
- scientific-writing — 89% identical, 0 lines differ
- scientific-writing — 89% identical, 19 lines differ
How it starts
The opening of the file, as written. The whole thing — 374 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Scientific Writing
Purpose
Produce clear scientific prose without inventing evidence or concealing uncertainty. Keep drafting, evidence verification, and submission approval as separate stages.
The accountable human authors control scientific decisions and final approval. AI is not an author, and generated fluency is never evidence [SW-S01, SW-S03].
Non-negotiable safety rules
Confidentiality
Do not send unpublished manuscripts, peer-review or editorial material, sensitive or restricted data, PHI or other personal data, proprietary content, or source documents to an external service without:
- explicit authorization from a person or body empowered to grant it; and
- a documented review of journal, institutional, funder, consent, ethics, contractual, legal, and data-use policy.
When authorization or policy is unclear, keep processing local and use only the minimum
metadata needed. De-identification requires expert review; removing obvious names is
not sufficient. See references/authorship_ai_confidentiality.md.
No fabrication
Never invent or complete:
- citations, references, DOI, PMID, PMCID, ISBN, URLs, or quotations;
- results, data values, denominators, sample sizes, units, effect estimates, uncertainty, statistical tests, or significance claims;
- methods, materials, protocol details, software versions, analysis choices, or deviations;
- registrations, approvals, consent, ethics statements, participant details, or dates;
- authors, author order, CRediT roles, acknowledgments, or permissions;
- funding, sponsor roles, conflicts, data or code availability, or AI disclosures.
Use an explicit missing, unverified, or not-applicable state. Do not substitute plausible boilerplate.
Evidence binding
Every factual or numeric manuscript claim must map to verified evidence IDs. A human verifier must open the source, confirm the proposition and locator, verify bibliographic metadata, and record who verified it and when.
Search snippets, generated summaries, memory, and another work's bibliography may aid
discovery but do not verify a claim. See references/evidence_workflow.md.
What ships with it
30 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.
- assets/authorship_template.json 1.2 KB
- assets/claim_evidence_template.csv 218 B
- assets/consistency_manifest_template.json 891 B
- assets/manuscript_manifest_template.json 1012 B
- assets/manuscript_scaffold.md 1.9 KB
- assets/REPORT_FORMATTING_GUIDE.md 2.6 KB
- assets/reporting_coverage_template.json 189 B
- assets/reporting_guidelines.json 16 KB
- assets/source_manifest_template.json 599 B
- references/authorship_ai_confidentiality.md 4.4 KB
- references/citation_styles.md 3.7 KB
- references/cli_reference.md 3.5 KB
- references/evidence_workflow.md 3.8 KB
- references/figures_tables.md 3.8 KB
- references/imrad_structure.md 4.4 KB
- references/journal_policies.md 2.5 KB
- references/professional_report_formatting.md 3.2 KB
- references/reporting_guidelines.md 4.7 KB
- references/research_integrity_open_science.md 4.1 KB
- references/source_ledger.md 9.9 KB
- references/writing_principles.md 3.8 KB
- scripts/_common.py 7.5 KB runs code
- scripts/audit_claims.py 8.6 KB runs code
- scripts/check_consistency.py 14 KB runs code
- scripts/check_references.py 6.9 KB runs code
- scripts/lint_manuscript.py 5.7 KB runs code
- scripts/scaffold_manuscript.py 4.2 KB runs code
- scripts/select_reporting_guidelines.py 7.4 KB runs code
- scripts/validate_authorship.py 11 KB runs code
- scripts/validate_manifest.py 14 KB runs code
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 · 374 lines · 60 tokens per session scan A f6026e7d79cd
scientific-writing is a skill published in the GitHub repository K-Dense-AI/scientific-agent-skills (44,469 stars, last pushed today), licensed MIT. It adds 60 tokens to every session and 3,004 once invoked, about $0.0003 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 2026-09-03.
Other skills, from other repositories
discovery-toolbox
A routed repertoire of 90 scientific thinking operators for biological research agents - visual reasoning, detectability and information budgets, search reframing, causal identification, competing explanations, observation and selection processes, pipeline artifact diagnosis, effort allocation, and confirmation…
discovery-director
Operate as a research director making original discoveries from a given biological question and dataset. Use when the task is open-ended scientific research, exploring omics or experimental data for findings, hypothesis generation and testing, screening a large candidate space of genes, variants, features or…
polars-dovmed
Search PMC Open Access and bioRxiv corpora with polars-dovmed. Use when structured, reproducible literature queries should run through the hosted API or local parquet indexes.
bio-interdomain-hgt
Detect and polarize interdomain horizontal gene transfer with homology, context, and phylogenetic checks. Use when studying lateral gene transfer, virus-host gene exchange, endogenous viral elements, or donor direction.
csag-extraction
Extract a Conditional Scientific Argumentation Graph and grounded Q&A from a manuscript. Use when representing assertions, contexts, evidence links, and inference steps in machine-readable form.
exploratory-data-analysis
Inspect scientific data and generate a Markdown structure-and-quality report. Use when triaging tabular, array, sequence, HDF5, JSON, or raster files before downstream analysis.