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 exon-research/genomi --skill rare-disease-cancergit clone --depth 1 https://github.com/exon-research/genomiWrote 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/exon-research/genomi/rare-disease-cancer)<a href="https://agentmods.dev/skills/exon-research/genomi/rare-disease-cancer"><img src="https://agentmods.dev/badge/skills/exon-research/genomi/rare-disease-cancer/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/exon-research/genomi/rare-disease-cancer"><img src="https://agentmods.dev/badge/skills/exon-research/genomi/rare-disease-cancer.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 | $0.00037 | $0.02319 |
| Opus 5 | $0.00018 | $0.01159 |
| Sonnet 5 | $0.00007 | $0.00464 |
| Haiku 4.5 | $0.00004 | $0.00232 |
Grade A, and why
rare-disease-cancer 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 12d 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 — 202 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Condition Review
Use this skill when the user asks about rare disease, hereditary disease, cancer risk genes, hereditary cancer, GeneCards-style gene context, MalaCards disease context, HPO/phenotype-to-disease review, HPO-style phenotype-to-gene review, carrier-relevance evidence, observed-condition review, or disease-gene source review.
Not for common-trait phenotypes. Common, complex-disease, GWAS-style, or drug-target candidate-gene questions use the matching source-specific tool. Use this skill when the phenotype is explicitly rare/Mendelian, HPO-style, or hereditary cancer.
Contract
Support both public-only questions and selected active genome evidence.
- Public-only questions stay public-only.
- Active genome evidence is used only when the current chat has selected or approved active genome access.
- GeneCards and MalaCards are context sources, not clinical-validity sources by themselves.
- Cancer-gene role, somatic cancer evidence, and inherited germline risk remain separate unless a reviewed source links them.
- Carrier-review output consumes ClinVar
carrier_relevancegroups and ranks review targets by evidence strength plus missing interpretation gates. - Observed-condition review consumes observed-condition, uncertainty/conflict, risk-association, benign/counterevidence, and population-context groups.
- Reviewed source findings are stored before final interpretation or reporting.
- HPO and symptom overlap can prioritize review targets, but it is not a diagnosis.
First Tool
Call phenotype.plan_risk_investigation first. Provide any public targets the user gave:
phenotype.plan_risk_investigationwith{"question":"BRCA1 hereditary breast cancer risk","gene":"BRCA1","investigation_type":"cancer_risk"}phenotype.plan_risk_investigationwith{"question":"carrier relevance review","investigation_type":"carrier_review"}phenotype.plan_risk_investigationwith{"question":"observed ClinVar condition review","investigation_type":"observed_condition_review"}
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.
- 12d ago First seen · 202 lines · 37 tokens per session scan A 7c038f31e20f
rare-disease-cancer is a skill published in the GitHub repository exon-research/genomi (482 stars, last pushed 11d ago), licensed Apache-2.0. It adds 37 tokens to every session and 2,319 once invoked, about $0.0002 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.
Other skills, from other repositories
release-doi
A release procedure for research repositories that publish versions with a DOI, a permanent identifier for scholarly work, through Zenodo.
autoresearch
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experiment
Run a materials-science / ML compute job on Rockie GPU capacity. Trigger words "run experiment", "submit job", "/experiment", or requests to quote/approve GPU spend before an experiment. Picks the right GPU type and count from a natural-language description (DFT for QE/VASP/ABINIT, MD for GROMACS/LAMMPS/OpenMM…
physics
Route physics simulation, modeling, validation, and research-compute requests across force fields, molecular dynamics, electronic structure, particle transport/collision, continuum multiphysics, plasma/PIC, nuclear/radiation, and astro/cosmology. Use open-source-first engines, refuse local heavyweight execution on the…
sota-delta
Track 3 quickstart wrapper that reproduces a paper or repository baseline on Rockie GPU, then extends it with a user-specified delta and compares baseline versus delta.
post-run-review
After an experiment finishes, structured review emits {isbug, failureclass, summary, metric, lowerisbetter}, auto-closes the journal node, emits a [LEARN] block when isbug=true, and files a [DEAD-END] when the failureclass is "bad-hypothesis". Use immediately after any training/eval run — the agent invokes this…