Install the "genomilab" agent skill from https://github.com/exon-research/genomi/tree/master/skills/genomilab into .claude/skills/genomilab/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "genomilab", then confirm the skill loads.
Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
skills CLI
$ npx skills add exon-research/genomi --skill genomilab -a codex
Project install goes to .agents/skills/; add -g for ~/.codex/skills/.
Install the "genomilab" agent skill from https://github.com/exon-research/genomi/tree/master/skills/genomilab into .agents/skills/genomilab/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "genomilab", then confirm the skill loads.
Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
skills CLI
$ npx skills add exon-research/genomi --skill genomilab -a cursor
Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.
Install the "genomilab" agent skill from https://github.com/exon-research/genomi/tree/master/skills/genomilab into .cursor/skills/genomilab/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "genomilab", then confirm the skill loads.
Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
skills CLI
$ npx skills add exon-research/genomi --skill genomilab -a gemini-cli
Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.
Install the "genomilab" agent skill from https://github.com/exon-research/genomi/tree/master/skills/genomilab into .gemini/skills/genomilab/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "genomilab", then confirm the skill loads.
Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
GitHub CLI
$ gh skill install exon-research/genomi genomilab
Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
skills CLI
$ npx skills add exon-research/genomi --skill genomilab -a github-copilot
Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.
Install the "genomilab" agent skill from https://github.com/exon-research/genomi/tree/master/skills/genomilab into .github/skills/genomilab/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "genomilab", then confirm the skill loads.
GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
skills CLI
$ npx skills add exon-research/genomi --skill genomilab -a opencode
OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
Install the "genomilab" agent skill from https://github.com/exon-research/genomi/tree/master/skills/genomilab into .opencode/skills/genomilab/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "genomilab", then confirm the skill loads.
OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
Skill name
genomilab
GitHub stars
484
Token cost
~4.2k tokens
SKILL.md length
2,044 words
Files
2
Skills in repo
20
Repo updated
First seen
Licence
Apache-2.0
At a glance
Run or continue patient-authorized, genome-informed GenomiLab investigations in the current Claude, Codex, or other MCP agent task.
Works in 5 steps: Call genomilab.open_workspace. → If it returns status="setup_required",… → Show the returned portal link when the… → …
A patient asks to open the Research Desk
SKILL.md covers Start or resume, Chair the specialist board, One investigation authorization and Plan and execute, plus 5 more sections
Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Genomilab is an agent skill from exon-research/genomi. Run or continue patient-authorized, genome-informed GenomiLab investigations in the current Claude, Codex, or other MCP agent task. Use when a patient asks to open the Research Desk, investigate a condition against their active genome, review an existing investigation, supply follow-up information, revise a hypothesis, or publish a revised investigation response.
Its SKILL.md is about 4.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `agents/openai.yaml`).
It sits in Research & Science, covering Bioinformatics. It works with Model Context Protocol. The repository describes itself as: Local-first, open-source Claude Science alternative, before Claude Science is a thing. Turn your AI agent into personal DNA expert. The licence is Apache-2.0.
When your agent uses it
A patient asks to open the Research Desk
Investigate a condition against their active genome
Review an existing investigation
Supply follow-up information
Example prompts
“/genomilab”
Workflow steps
5 steps, taken from the first numbered list in SKILL.md.
1Call genomilab.open_workspace.
2If it returns status="setup_required", keep setup in core Genomi. Select
3Show the returned portal link when the patient needs onboarding or approval.
4Call genomilab.create_investigation for a new question, or
5If no profile observation exists, ask for one concise patient-reported fact
What it can do on your machine
Read from SKILL.md and the folder at commit 1df4f5b. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are json).
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Genomilab loads about 4.2k tokens when it runs. Until then it costs about 94 tokens; SKILL.md has 2,044 words of instructions outside code blocks.
Always· name and description, kept in context so the agent knows when to use it
~94
When it runs· the whole SKILL.md, loaded when a task matches
~4.2k
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
Download SKILL.mdSave it as .claude/skills/genomilab/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
genomilab
description
Run or continue patient-authorized, genome-informed GenomiLab investigations in the current Claude, Codex, or other MCP agent task. Use when a patient asks to open the Research Desk, investigate a condition against their active genome, review an existing investigation, supply follow-up information, revise a hypothesis, or publish a revised investigation response.
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
Call genomilab.open_workspace.
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.
Show the returned portal link when the patient needs onboarding or approval.
Call genomilab.create_investigation for a new question, or
genomilab.inspect_investigation for an existing investigation.
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.
On resume, inspect the investigation first. Treat its pre-authorization
specialist_board as a structural redacted marker only: board existence plus
status and member_count; a static chair description may also appear. If
that marker says a board exists, do not call
genomilab.form_specialist_board again. Renew current-session authorization
through the flow below. After private_context_status is
approved_for_session, inspect again; only then read and reuse the full
specialist IDs, roles, tasks, and current-work states, and reconstitute the
corresponding native subagents if the host requires it.
The chair alone owns the patient conversation, authorization, all private AGI
reads, and canonical plan, hypothesis, gap, and brief commits. Give specialists
public questions or only the minimum approved evidence needed for their task.
Specialists return their analysis to the chair; they never read the AGI
directly, interact with the portal, request patient approval, or commit the
canonical investigation artifacts.
Call genomilab.report_specialist_progress with the current round_id only at
meaningful work milestones, using working, blocked, or completed and a
short current_work label.
GenomiLab derives the initial assigned state. Do not send raw agent messages,
chain of thought, token streams, native task IDs, or per-call chatter. The
portal monitors only these committed board milestones.
When a specialist returns, use genomilab.record_specialist_report to commit
that round's findings and gaps with exact evidence and profile anchors. A
specialist report is traceable synthesis, not a new evidence record or a
clinical conclusion. Commit all assigned reports before starting another round.
One investigation authorization
Call genomilab.prepare_authorization after the patient profile contains the
facts needed for the question. The portal presents the exact selected profile
slice, current genome scope, and current underlying-agent destination.
Give the patient the portal launch link returned by that call: its one-time
token targets the exact signed candidate, while the candidate itself remains
redacted from the agent-facing result and URL. Do not prepare another candidate
merely to display the review.
For an existing investigation in a new agent session, omit
observation_revision_ids to renew the pinned profile, AGI, scope, and purpose
without silently expanding to newer profile facts. Use
genomilab.record_patient_observations for an intentional context update.
Each local stdio MCP initialize handshake is a new GenomiLab agent session.
It closes the prior session's private authority even if the host reports the
same client name and version, so do not reinitialize the stdio MCP connection
mid-investigation. HTTP MCP initialization is public-tools-only and cannot
create or replace the private GenomiLab runtime.
The agent must not approve this candidate. Ask the patient to review it in the
portal, then poll with genomilab.inspect_investigation. Continue when
private_context_status is approved_for_session.
Do not request another approval for routine local planning, evidence work,
hypothesis updates, or brief publication. A new patient approval is appropriate
only when the profile or genome snapshot/scope changes. Exact external-provider
egress can require a separate just-in-time portal approval.
Plan and execute
Read capability_catalog from genomilab.inspect_investigation. Submit only
requests that are currently advertised as available:
genomilab.submit_plan validates and accepts the exact requests under the
active investigation authorization and requires the specialist board to exist.
Each accepted plan version is one immutable investigation round. Supply one
focus question and exactly one assignment for every persistent specialist.
The chair submits the canonical plan. Do not invent capability parameters or
resend modified parameters to execution. Call genomilab.execute_request with
only the investigation and request IDs.
When the approved genomic scope advertises
genomi.variant.find_gene_variants, the phenotype specialist may return a
bounded candidate set to the chair, but the chair alone submits and executes
the request. Use 1–10 canonical gene symbols, the exact AGI/build fields shown
by the catalog, and candidate_set_lineage naming that persistent specialist
plus the exact current profile/evidence anchors used. GenomiLab fingerprints
the actual set and lineage in the committed personal-genome evidence. Do not
give the specialist the AGI result or direct genome access.
When a request returns:
completed: inspect the new investigation state and continue.
in_progress: call genomilab.check_request with the same request ID.
approval_required: show the portal link and ask the patient to approve the
exact external disclosure there. Do not add an approved argument yourself.
source_unavailable or an unavailable capability: state the evidence gap;
do not treat it as negative biomedical evidence.
Re-inspect after evidence commits. The capability catalog may then advertise
new exact disease-relation, hypothesis, or gap templates. Submit a new bounded
plan when later synthesis depends on those newly available records.
Publish the investigation response
Use the hypothesis and gap capabilities advertised by the investigation
catalog. Preserve source priors and cite the exact profile and evidence anchors.
Use supersedes_hypothesis_id when revising an existing hypothesis.
Read brief_authoring.brief_schema from the latest authorized
genomilab.inspect_investigation result. Build the brief argument from that
exact context-bound schema and the published investigation records. Omit
modality_badges; GenomiLab derives them from the cited records. Then call
genomilab.submit_brief. Treat the returned investigation_response as the
durable research record; answer the patient conversationally in the current
host task. Keep all health language informational and preserve the required
clinical boundary. Build timeline from exact evidence/profile anchors and
write case-specific clinician_questions with their motivating evidence,
profile, hypothesis, and gap identifiers; do not substitute generic canned
questions. The portal can print the current brief or download a self-contained
HTML copy for the patient to take to a treating professional.
Patient follow-up and revision
When the patient supplies additional information in the current conversation:
Call genomilab.record_patient_observations with the same investigation ID.
Each observation needs at least modality and label or
original_wording. Use patient wording and patient-reported provenance.
For a correction, include supersedes_observation_revision_id on that one
observation. Otherwise record a new observation.
Ask the patient to approve the returned context delta in the portal once.
Re-inspect after approval. Replan and rerun only evidence affected by the
changed context.
Register a revised hypothesis with supersedes_hypothesis_id, then publish
brief version 2. Explain what changed and what did not.
Keep the same host task and investigation ID throughout this flow.
Show full SKILL.md (780 more words)Show less
Research tools
Call genomilab.list_research_tools when provider availability matters.
Paperclip supports approved investigation-scoped literature search/lookup,
regulatory search, and trial-registry search when the returned capability
catalog advertises the exact route. It does not provide full-text extraction
or claim verification. A saved or verified credential is not a live route;
without owner deployment authorization, an independent patient-data
contract, and their configuration, state the route is unavailable. Every
actual request also requires patient approval of its exact disclosure.
Biohub and Modal connection checks are setup checks only. Never describe one
as an ESM or Proto scientific run.
Use genomilab.verify_sequence_substitution first to bind an intended
substitution to a public reference protein. Genomi stores only sequence
digests and normalized descriptors in the round-bound research ledger.
Use genomilab.run_esm_substitution_analysis only when
scientific_operations advertises it as available. It invokes the configured
local, network-disabled scientific executor; otherwise it returns an explicit
unavailable state and creates no artifact.
Use genomilab.run_proto_blinded_experiment_design under the same rule for a
bounded blinded experimental design. It is not a general sequence-design
surface.
ESM, Proto, Genomi verification, and unverified host submissions are
nonclinical research artifacts. They cannot support hypotheses, evidence,
answer-readiness, brief claims, treatment content, or clinician export.
Provider credentials and connect/disconnect actions stay in the patient portal
and must never appear in agent tool arguments or responses.
Revocation and cancellation
Use genomilab.revoke_context when the patient revokes private investigation
access. This blocks future GenomiLab profile and genome operations. Cancel or
stop the native task with the underlying host's own task controls; do not claim
that portal revocation cancelled the host task.
Operation reference
genomilab.open_workspace
Check the current user and query-ready AGI, bind the current MCP host, and
return the loopback portal link when requested.
genomilab.create_investigation
Create the durable investigation record for the patient's question. This does
not create or start another agent task.
genomilab.form_specialist_board
Record the 2–5 persistent logical specialist IDs, explicit roles, and bounded
initial tasks for the
native board formed by the chair. Call once for a new investigation; reuse the
recorded board on resume.
genomilab.report_specialist_progress
Commit a specialist's meaningful working, blocked, or completed milestone
for the current round_id, with a short current-work label for portal
monitoring. Completion is terminal within that round but the same persistent
specialist can receive a new assignment in the next round. This is not
agent-message, reasoning, token, or native-task streaming.
genomilab.record_specialist_report
Commit one immutable findings-and-gaps report for a specialist assigned to the
current round. Findings cite exact current-round evidence or profile records;
gaps may identify still-missing evidence. This report is synthesis only and
cannot substitute for an evidence record.
genomilab.inspect_investigation
Read current context, plan, evidence, hypotheses, briefs, domain events,
capability catalog, context-bound brief authoring schema, and next actions.
Before current-session authorization, an existing board is only a structural
redacted marker; inspect again after authorization to read its full assignments.
genomilab.prepare_authorization
Prepare the exact context candidate for patient review in the portal. Omit
observation_revision_ids for a new-session renewal of an already pinned
investigation. For an initial authorization, omit it only when every current
profile fact is relevant.
genomilab.record_patient_observations
Record patient-provided facts for either initial onboarding or a later turn,
then prepare the required initial or delta context authorization.
genomilab.submit_plan
Submit the round focus, one assignment for every persistent specialist, and the
advertised capability names with their exact catalog parameters as immutable
request IDs. The accepted plan version and investigation round are the same
unit of work.
genomilab.execute_request
Execute one accepted request ID. Never alter or resend its parameters here.
genomilab.check_request
Poll the same accepted request ID only after it returns in_progress.
genomilab.submit_brief
Commit the exact brief advertised by the latest authorized inspection. Claims
cite current evidence, profile, hypothesis, and gap identifiers; GenomiLab
derives modality badges and preserves the clinical boundary.
genomilab.submit_research_artifact
Persist a round-bound unverified host artifact with its
exact method, model, versions, input/output digests, and provenance. This route
never verifies scientific or provider execution.
genomilab.verify_sequence_substitution
Verify an intended protein substitution against a supplied public reference
protein sequence using deterministic local Genomi rules. The sequence is
transient; the ledger stores only hashes and normalized descriptors.
genomilab.run_esm_substitution_analysis
Run the same-round verified substitution through the configured bounded local
ESM executor. Treat status="unavailable" as no execution and no result.
genomilab.run_proto_blinded_experiment_design
Run a bounded same-round blinded-design request through the configured local
Proto executor. Treat status="unavailable" as no execution and no result.
genomilab.list_research_artifacts
Read the investigation's current round-bound nonclinical research artifacts,
including their method, model, version, input/output, provenance, and fixed use
boundaries. These records are not evidence, hypothesis support, brief claims,
answer-readiness inputs, or clinician-export content.
genomilab.list_research_tools
Inspect provider connection state and scientific-operation availability as
separate facts. Connection readiness never proves scientific execution.
genomilab.revoke_context
Revoke future GenomiLab access to the investigation's private context. Use the
host's own controls separately if the native task must stop.
Genomilab next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
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Run or continue patient-authorized, genome-informed GenomiLab investigations in the current Claude, Codex, or other MCP agent task. Genomilab is an agent skill from exon-research/genomi. Run or continue patient-authorized, genome-informed GenomiLab investigations in the current Claude, Codex, or other MCP agent task.
When should I use Genomilab?
Genomilab fits situations like: A patient asks to open the Research Desk; investigate a condition against their active genome; review an existing investigation; supply follow-up information.
How do I install Genomilab in Claude Code?
Run `npx skills add exon-research/genomi --skill genomilab -a claude-code`. Or copy the skill folder (skills/genomilab in exon-research/genomi) into .claude/skills/genomilab in your project. Claude Code loads it when a task matches its description.
How do I install Genomilab in Codex?
Run `npx skills add exon-research/genomi --skill genomilab -a codex`. Or copy the skill folder (skills/genomilab in exon-research/genomi) into .agents/skills/genomilab in your project. Codex loads it when a task matches its description.
Can I use Genomilab in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add exon-research/genomi --skill genomilab -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/genomilab, .gemini/skills/genomilab, .github/skills/genomilab and .opencode/skills/genomilab in your project.
What does Genomilab need to run?
SKILL.md names no scripts, command-line tools or credentials: Genomilab is instructions for the agent only.
Does Genomilab access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Genomilab safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Genomilab use?
Genomilab is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Genomilab use?
About 4.2k tokens (SKILL.md is roughly 17k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Genomilab?
Skills that share tags, products or a category with Genomilab: Hcls Build Agent (aws-samples/amazon-bedrock-agents-healthcare-lifesciences, 274 stars), Tooluniverse (ynulihao/AgentSkillOS, 618 stars), Remote Compute Ssh (aipoch/open-science, 5.5k stars) and Latchbio Integration (K-Dense-AI/scientific-agent-skills, 48k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Genomilab?
exon-research (a GitHub organization) maintains it in exon-research/genomi, which has 484 GitHub stars. The repository holds 20 skills in this directory. The repository was last updated on August 31, 2026.
Source: exon-research/genomi on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.