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 analytical-groundinggit 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/analytical-grounding)<a href="https://agentmods.dev/skills/exon-research/genomi/analytical-grounding"><img src="https://agentmods.dev/badge/skills/exon-research/genomi/analytical-grounding/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/analytical-grounding"><img src="https://agentmods.dev/badge/skills/exon-research/genomi/analytical-grounding.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 16 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00026 | $0.01041 |
| Opus 5 | $0.00013 | $0.00521 |
| Sonnet 5 | $0.00005 | $0.00208 |
| Haiku 4.5 | $0.00003 | $0.00104 |
Grade A, and why
analytical-grounding 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 10d 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 — 101 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Analytical Grounding
Use this skill for source-declared records that ground an analytical statement, without asking Genomi to choose the interpretation.
Use When
- The input is a controlled pathway or gene-set name/id and the agent needs its canonical member genes.
- The input is a controlled cell type and the agent needs marker-gene records.
- The input is a genomic interval and the agent needs overlaps against declared GENCODE or ENCODE annotation files.
Operations
pathway.retrieve_members: retrieve Reactome, KEGG human pathway, or supplied or installed MSigDB Hallmark GMT member genes. Use a source for free-text pathway names unless the identifier prefix makes the source clear.cell_type.retrieve_markers: retrieve HPA single-cell marker records, installed CellMarker/PanglaoDB tables, or supplied marker tables.region.retrieve_features: retrieve interval overlaps from supplied or installed GENCODE GTF and/or ENCODE cCRE BED files for GRCh37/GRCh38. Supplyassembly; without it the tool reports unsupported assembly instead of guessing a genome build.
Boundaries
- These are retrieval verbs over declared source coverage.
- Do not use them as experimental protocol recommendations, workflow templates, or free-text biological interpretation.
- Treat
coverage_statusliterally:data_returned: declared source records were returned.in_scope_empty: the input was in declared scope, and no records matched.out_of_scope_for_input: the source, assembly, identifier, or required source file is outside declared coverage.
- Preserve source priors. A pathway member, marker gene, interval overlap, or druggable-target membership row is evidence context, not a selected answer.
Examples
pathway.retrieve_memberswith{"pathway_id_or_name":"R-HSA-70635"}pathway.retrieve_memberswith{"pathway_id_or_name":"hsa00010"}cell_type.retrieve_markerswith{"cell_type_id_or_name":"hepatocytes","source":"hpa"}cell_type.retrieve_markerswith{"cell_type_id_or_name":"Hepatocyte","source":"cellmarker"}region.retrieve_featureswith{"region":"1:1000-1250","assembly":"GRCh38"}
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.
- 10d ago First seen · 101 lines · 26 tokens per session scan A afdda0e9f962
analytical-grounding is a skill published in the GitHub repository exon-research/genomi (482 stars, last pushed 9d ago), licensed Apache-2.0. It adds 26 tokens to every session and 1,041 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.
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
Canonical around-the-clock research loop. Defines the agent's outer loop — read taste corpus + queue, pick the next experiment, mutate the explicitly-declared mutation surface, run the experiment under a hard time budget against a frozen metric, score, codify, repeat. Augmented with Karpathy's sharp primitives (frozen…
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…
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.
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…
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…