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 onekgpdgit 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/onekgpd)<a href="https://agentmods.dev/skills/k-dense-ai/scientific-agent-skills/onekgpd"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agent-skills/onekgpd/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/onekgpd"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agent-skills/onekgpd.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- 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 | $0.00143 | $0.05700 |
| Opus 5.5 | $0.00057 | $0.02280 |
| Sonnet 5.5 | $0.00029 | $0.01140 |
| Haiku 4.5 | $0.00014 | $0.00570 |
Grade A, and why
onekgpd 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 — 430 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OneKGPd: Individual-Level Queries over the 1000 Genomes Project
Scope
This skill queries the 1000 Genomes Project dataset — the extended high-coverage cohort
of 3,202 whole-genome-sequenced individuals, on the GRCh38 assembly. All results
are drawn from this cohort, and sample names returned by the skill (for example
HG00096 or NA21130) identify its participants.
Queries resolve against the cohort's per-individual genotype data. This supports two complementary classes of question: selecting variants carried within a region (across the whole cohort or within a specified set of individuals), and selecting the individuals who carry variants matching given criteria. Variant selection can be filtered by allele frequency, predicted consequence, clinical significance, AlphaMissense classification, and the other annotation axes listed below. Relatedness between two named individuals is also available.
The genotype state in which a variant is carried — heterozygous or homozygous — is a criterion that queries may specify; results are returned as variants or as sample names, not as raw genotypes.
The public service is TLS gRPC at db.dnaerys.org:443, accessed with
dnaerys 0.2.1 (Python 3.11+); it is not a REST base URL. The maintained
service snapshot advertises VEP 115 / GENCODE 49, ClinVar 202502, and gnomAD
4.1. These are the service's annotation releases, not the latest release of
each upstream resource. Record them when interpreting results.
When to Use
Use this skill when you need to:
- Find variants carried in a region or set of regions matching some criteria
across the whole cohort (
select-variants). - Find variants carried in a region or set of regions matching some criteria
in specific set of individuals (
select-variants-in-samples). - Find which 1000 Genomes individuals carry variants matching some criteria
in a region or set of regions (
select-samples). - Count how many individuals carry specific variants (
count-samples). - Restrict any variant query to heterozygous-only or homozygous-only carriage, or query both together (default).
- Identify which individuals are homozygous reference at a single position
(
select-samples-hom-ref). - Determine the relatedness between two named 1000 Genomes individuals —
both the degree (twin / 1st / 2nd / 3rd / unrelated) and the KING kinship
coefficient (
kinship). - Get dataset totals — sample count, sex split, variant count, assembly
(
dataset-info). - Variant selection can be specified by KGP allele frequency, gnomAD 4.1 exome and gnomAD 4.1 genome allele frequency, AlphaMissense Score and AlphaMissense Class, ClinVar significance (202502), and VEP annotations (impact, biotype, feature type, variant class, consequences).
What ships with it
5 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.
- 25d ago Changed · +49 lines 6a7c0a90c42e
- 26d ago Changed · +10 lines 023710eb709e
- 1mo ago First seen · 371 lines · 143 tokens per session scan A 918797c80e98
onekgpd is a skill published in the GitHub repository K-Dense-AI/scientific-agent-skills (54,777 stars, last pushed today), licensed MIT. It adds 143 tokens to every session and 5,700 once invoked, about $0.0006 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 2026-09-03.
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…
bio-interdomain-hgt
Detect and polarize interdomain horizontal gene transfer with reciprocal hits, genomic context, and gene trees. Use for virus-host gene exchange, endogenous viral elements, or donor direction.
scholion
Second-opinion support for individuals and clinicians, one person's data at a time — genome, laboratory history, prescriptions, wearables. It reads them locally and states what the data cannot support. No data is baked into the skill: everyone supplies their own. Use it when you need to check a physician's…
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.
notebooks
Author, run and convert marimo or Jupyter notebooks. Use when delivering an analysis notebook executed end to end with figures embedded.