synthetic-sciences/openscience is an AI workbench that carries out scientific research by reading papers, forming hypotheses, writing and running code, conducting experiments, analyzing results, and preparing reports. Researchers use it for work in machine learning, biology, physics, and chemistry with remote or local models. Catalogue add-ons extend its scientific workflows through skills and 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 synthetic-sciences/openscience --skill onekgpdgit clone --depth 1 https://github.com/synthetic-sciences/openscienceWrote 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/synthetic-sciences/openscience/onekgpd)<a href="https://agentmods.dev/skills/synthetic-sciences/openscience/onekgpd"><img src="https://agentmods.dev/badge/skills/synthetic-sciences/openscience/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/synthetic-sciences/openscience/onekgpd"><img src="https://agentmods.dev/badge/skills/synthetic-sciences/openscience/onekgpd.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 | $0.00143 | $0.04894 |
| Opus 5.5 | $0.00057 | $0.01958 |
| Sonnet 5.5 | $0.00029 | $0.00979 |
| Haiku 4.5 | $0.00014 | $0.00489 |
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 1mo 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
98% identical to onekgpd — 116 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 — 378 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.
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.
- 1mo ago Changed · +5 lines b79a6a12b5ee
- 1mo ago First seen · 373 lines · 143 tokens per session scan A a3dada8fdb16
onekgpd is a skill published in the GitHub repository synthetic-sciences/openscience (4,025 stars, last pushed today), licensed Apache-2.0. It adds 143 tokens to every session and 4,894 once invoked, about $0.0006 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 98% identical to onekgpd, differing in 116 lines, and is treated as a copy.
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