genomilab

A research workspace for patient-approved investigations that use a person’s selected genome data to study a health question.

In plain words
What is it for?
It helps open or continue investigations, review existing work, manage evidence and hypotheses, and prepare validated summaries for the patient portal.
Why use it?
It keeps genome access, approvals, evidence, follow-up questions, and investigation results organized in one continuing task.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/exon-research/genomi/genomilab
Any agent
npx skills add exon-research/genomi --skill genomilab
Clone the repo
git clone --depth 1 https://github.com/exon-research/genomi

Made for: Claude Code, Codex.

Per session 72 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,452 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00072 $0.03452
Opus 5 $0.00036 $0.01726
Sonnet 5 $0.00014 $0.00690
Haiku 4.5 $0.00007 $0.00345

Measured yesterday against content hash f486ca16cc4c, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

genomilab 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 yesterday.

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.

skills/genomilab/SKILL.md · 347 lines

How it starts

The opening of the file, as written. The whole thing — 347 lines — stays where its author put it; the contents beside it link to each section on GitHub.

GenomiLab Research Desk

Keep the current host agent in control of the conversation, native specialist subagents, planning, streaming, follow-ups, and cancellation. Use GenomiLab for typed capabilities, patient authorization, Active Genome Index access, durable evidence and hypothesis state, validated briefs, and the patient portal.

The portal is for patient onboarding, exact approvals, integration setup, and monitoring committed investigation milestones. Never start a second agent task from the portal.

Start or resume

  1. Call genomilab.open_workspace.
  2. If it returns status="setup_required", keep setup in core Genomi. Select or finish the current user's Active Genome Index. If none exists, ask the user for the local VCF or another supported genome-source path and use core Genomi intake; pointing the host at that path is the only genome handoff. Do not open an investigation without a query-ready selected index.
  3. Show the returned portal link when the patient needs onboarding or approval.
  4. Call genomilab.create_investigation for a new question, or genomilab.inspect_investigation for an existing investigation.
  5. If no profile observation exists, ask for one concise patient-reported fact before preparing authorization. Do not fabricate a symptom, diagnosis, phenotype, family history, or molecular finding.

Do not ask for a VCF path in GenomiLab. Genome intake remains in core Genomi; GenomiLab uses the selected Active Genome Index.

Chair the specialist board

For every new investigation, act as chair and form 2–5 native host subagents with adaptive, non-overlapping domain roles. Give each specialist an explicit role and bounded task chosen for the question; do not use a fixed board when a different evidence mix is more relevant. Use stable logical specialist_id values, not native task or thread identifiers. Record the board once with genomilab.form_specialist_board before submitting a plan. These are persistent specialist identities: reuse the same IDs in every investigation round, while giving each specialist a new bounded assignment for that round.

Read the full file on GitHub · 347 lines

Files

What ships with it

1 file 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.

Changes

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.

  1. yesterday First seen · 347 lines · 72 tokens per session scan A f486ca16cc4c

Subscribe to this mod's changes

genomilab is a skill published in the GitHub repository exon-research/genomi (481 stars, last pushed 3d ago), licensed Apache-2.0. It adds 72 tokens to every session and 3,452 once invoked, about $0.0004 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.

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