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 source-researchgit 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/source-research)<a href="https://agentmods.dev/skills/exon-research/genomi/source-research"><img src="https://agentmods.dev/badge/skills/exon-research/genomi/source-research/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/source-research"><img src="https://agentmods.dev/badge/skills/exon-research/genomi/source-research.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 | $0.00027 | $0.01380 |
| Opus 5.5 | $0.00011 | $0.00552 |
| Sonnet 5.5 | $0.00005 | $0.00276 |
| Haiku 4.5 | $0.00003 | $0.00138 |
Grade A, and why
journal-source-research 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.
How it starts
The opening of the file, as written. The whole thing — 165 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Journal Source Research
Use this Journal sub-skill when a claim needs source context beyond local static rows: current ClinVar assertion, gene mechanism, inheritance, penetrance, guideline evidence, population tension, or literature/source conflict.
Goal
Review focused public targets and write reviewed findings back into the local
evidence DB before using them in final interpretation. In capability discovery,
these tools are part of journal because they create reusable investigation
memory rather than a separate evidence category.
Works with Active Genome Index context and public-only context. If Active Genome Index context exists, use its evidence DB for user-specific context. With public-only context, use the shared evidence DB and frame the answer as public-target source review.
Convention: See
skills/conventions/evidence-quality.md. Convention: Seeskills/_output-rules.md.
Contract
Contract:
- External research uses selected public targets only.
- API-backed sources are marked in tool
dependencyContract.externalNetwork; local source files are marked independencyContract.localResources. If an API source is unavailable, the tool returnssource_unavailable. - Reviewed source findings are written back before final interpretation.
- Shared evidence is reusable public-target knowledge.
- Private evidence is reserved for user-specific combinations and context.
- Public-only answers describe public-target evidence.
Cross-Capability Synthesis
A scope-limited result from this capability is not a final user-facing answer when other Genomi capabilities can contribute orthogonal evidence to the same question. Returning "cannot answer" while applicable capabilities remain unexamined is a host-agent failure mode.
Tools
gnomad.fetch_population_frequency
Fetch reusable gnomAD public population frequency for one allele and write it into evidence storage.
Use when: gnomAD population frequency would change interpretation of an exact public allele or candidate variant.
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 First seen · 165 lines · 27 tokens per session scan A 316d5d44141c
journal-source-research is a skill published in the GitHub repository exon-research/genomi (489 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 27 tokens to every session and 1,380 once invoked, about $0.0001 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 2026-08-30.
Other skills, from other repositories
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…
queue-refill
Refill the experiment queue when it drops below target (default 5 pending items). Brainstorms 3–5 new high-quality experiments informed by recent [LEARN] rules, killed dead-ends, best-so-far results, and hypothesis-calibration drift. Use when queue.py refill-needed returns non-zero, when the user asks "what should we…