Agent skill

Genomilab

by exon-research in exon-research/genomi

Run or continue patient-authorized, genome-informed GenomiLab investigations in the current Claude, Codex, or other MCP agent task.

Apache-2.0Auto-check passedResearch & Science

Install Genomilab

skills CLI
$ npx skills add exon-research/genomi --skill genomilab -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install exon-research/genomi genomilab --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/exon-research/genomi.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/genomilab .claude/skills/genomilab && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

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.

  1. Call genomilab.open_workspace.
  2. If it returns status="setup_required", keep setup in core Genomi. Select
  3. Show the returned portal link when the patient needs onboarding or approval.
  4. Call genomilab.create_investigation for a new question, or
  5. If 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.

SKILL.md

The full file from exon-research/genomi at commit 1df4f5b, republished under its Apache-2.0 licence (© exon-research). 2,044 words, ~4,205 tokens.

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

  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.

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:

json
{
  "investigation_id": "investigation-...",
  "focus_question": "What does the approved profile establish?",
  "specialist_assignments": [
    {
      "specialist_id": "specialist-timeline",
      "task": "Reconstruct the approved clinical timeline"
    },
    {
      "specialist_id": "specialist-evidence",
      "task": "Review relevant public evidence"
    }
  ],
  "requests": [
    {
      "id": "profile-review",
      "capability": "investigation.project_profile",
      "parameters": {}
    }
  ]
}

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:

  1. 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.
  2. For a correction, include supersedes_observation_revision_id on that one observation. Otherwise record a new observation.
  3. Ask the patient to approve the returned context delta in the portal once.
  4. Re-inspect after approval. Replan and rerun only evidence affected by the changed context.
  5. 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.

© exon-research, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file in skills/genomilab of exon-research/genomi.

  • SKILL.md
  • agents/openai.yaml

Open the folder on GitHubat commit 1df4f5b

Compare with similar skills

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Tooluniverseynulihao/AgentSkillOS6182 repos~2.5kAutomated safety check: PassNone
Remote Compute Sshaipoch/open-science5.5k—~5.7kAutomated safety check: PassApache-2.0
Latchbio IntegrationK-Dense-AI/scientific-agent-skills48k1 repos~2.5kAutomated safety check: NotesMIT
Hcls Get Startedaws-samples/amazon-bedrock-agents-healthcare-lifesciences274—~607Automated safety check: PassMIT-0

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Questions about Genomilab

What does Genomilab do?

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.