Queries JGI Lakehouse (Dremio) for genomics metadata from GOLD, IMG, Mycocosm, Phytozome.

Custom licenceAuto-check passedResearch & Science

Install Jgi Lakehouse

skills CLI
$ npx skills add BioTender-max/awesome-bio-agent-skills --skill jgi-lakehouse -a claude-code

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

GitHub CLI
$ gh skill install BioTender-max/awesome-bio-agent-skills jgi-lakehouse --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/BioTender-max/awesome-bio-agent-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/omics/jgi-lakehouse .claude/skills/jgi-lakehouse && 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
jgi-lakehouse
GitHub stars
200
Token cost
~3.7k tokens
SKILL.md length
1,147 words
Files
32 (incl. scripts, references)
Skills in repo
23
Repo updated
First seen
Licence
Custom licence

At a glance

Queries JGI Lakehouse (Dremio) for genomics metadata from GOLD, IMG, Mycocosm, Phytozome.

  • Works in 6 steps: Start from the assembly taxon OID → Pull the JGI/GOLD linkage fields from… → Prefer JAMO pmoid for JGI read lookup → …
  • Working with JGI data
  • SKILL.md covers Quick Start, When to Use, Best practices and Data Access: Lakehouse vs…, plus 12 more sections
  • Calls rg, python3 and pip; reaches lakehouse-1.jgi.lbl.gov and github.com

What it does

Jgi Lakehouse is an agent skill from BioTender-max/awesome-bio-agent-skills. Queries JGI Lakehouse (Dremio) for genomics metadata from GOLD, IMG, Mycocosm, Phytozome. Downloads genome files from JGI filesystem using IMG taxon OIDs and links JGI taxon OIDs to read files through PMO/GOLD identifiers and JAMO. Use when working with JGI data, GOLD projects, IMG annotations, or downloading genomes.

Its SKILL.md is about 3.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 33 other files, including scripts and reference files (for example `README.md`, `docs/IMG-tables-reference.md` and `docs/IMG_data_types.md`).

It sits in Research & Science, covering Bioinformatics and Data warehousing. It works with PostgreSQL and SQL. The repository describes itself as: A curated collection of AI agent skills for biomedical research, covering genomics, proteomics, single-cell analysis, clinical AI, and protein design.

When your agent uses it

  • Working with JGI data
  • IMG annotations
  • Downloading genomes

Example prompts

  • “Use the jgi-lakehouse skill to query JGI Lakehouse (Dremio) for genomics metadata from GOLD, IMG, Mycocosm, Phytozome”
  • “/jgi-lakehouse”

Requirements

  • Docker

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Start from the assembly taxon OID
  2. Pull the JGI/GOLD linkage fields from metadata
  3. Prefer JAMO pmoid for JGI read lookup
  4. Direct taxon-OID lookup is still useful
  5. spid is valid, but not sufficient
  6. Inspect and fetch the actual file

What it can do on your machine

Read from SKILL.md and the folder at commit 8cbdd18. 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

    Ships 1 file in scripts/, which the agent can run.

    Shell commands in SKILL.md call:

    • rg
    • python3
    • pip

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • lakehouse-1.jgi.lbl.gov
    • github.com

    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

Jgi Lakehouse loads about 3.7k tokens when it runs, and up to ~4k if it reads all its reference files. Until then it costs about 83 tokens; SKILL.md has 1,147 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~83
When it runs · the whole SKILL.md, loaded when a task matches
~3.7k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~4k

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); the scripts in this folder are not scanned.

SKILL.md

Its licence (Custom licence) doesn't allow us to republish the file, so here is its outline and opening line. It has 1,147 words (~3,725 tokens).

“What is it? JGI's unified data warehouse (651 tables) + filesystem access to genome files.”

— opening of SKILL.md by BioTender-max, Custom licence
name
jgi-lakehouse

Read the full SKILL.md on GitHub

Files

SKILL.md and 31 other files (scripts, references) in skills/omics/jgi-lakehouse of BioTender-max/awesome-bio-agent-skills.

  • SKILL.md
  • README.md
  • docs/IMG-tables-reference.md
  • docs/IMG_data_types.md
  • docs/arrow-flight-python.md
  • docs/authentication.md
  • docs/data-catalog.md
  • docs/explore_IMG_genomes.md
  • docs/explore_gold.md
  • docs/img_and_gold_terms.md
  • docs/large_metagenome_queries.md
  • docs/metagenome_comparability.md
  • docs/metagenome_metadata.md
  • docs/numg_metagenome_sequences.md
  • docs/phytozome.md
  • docs/sql-quick-reference.md
  • examples/01-find-16s-rrna-genes.md
  • examples/03-cross-database-joins.md
  • examples/04-download-img-genomes.md
  • … and 13 more

Open the folder on GitHubat commit 8cbdd18

Compare with similar skills

Jgi Lakehouse 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.

Jgi Lakehouse compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Jgi Lakehouse this skillBioTender-max/awesome-bio-agent-skills200—~3.7kAutomated safety check: PassCustom licence
Clickhouse Logs Queriessupabase/supabase111k—~2.4kAutomated safety check: PassApache-2.0
Chdb Datastorevemetric/vemetric3952 repos~1.4kAutomated safety check: PassApache-2.0
Chdb SQLvemetric/vemetric3951 repos~1.2kAutomated safety check: PassApache-2.0
Biomarker Database Analysisaws-samples/amazon-bedrock-agents-healthcare-lifesciences274—~1.1kAutomated safety check: PassMIT-0
Querying Tempotempoxyz/tidx108—~3.1kAutomated safety check: PassMIT

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Works with

Questions about Jgi Lakehouse

What does Jgi Lakehouse do?

Queries JGI Lakehouse (Dremio) for genomics metadata from GOLD, IMG, Mycocosm, Phytozome. Jgi Lakehouse is an agent skill from BioTender-max/awesome-bio-agent-skills. Queries JGI Lakehouse (Dremio) for genomics metadata from GOLD, IMG, Mycocosm, Phytozome.

When should I use Jgi Lakehouse?

Jgi Lakehouse fits situations like: working with JGI data; IMG annotations; downloading genomes.

How do I install Jgi Lakehouse in Claude Code?

Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill jgi-lakehouse -a claude-code`. Or copy the skill folder (skills/omics/jgi-lakehouse in BioTender-max/awesome-bio-agent-skills) into .claude/skills/jgi-lakehouse in your project. Claude Code loads it when a task matches its description.

How do I install Jgi Lakehouse in Codex?

Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill jgi-lakehouse -a codex`. Or copy the skill folder (skills/omics/jgi-lakehouse in BioTender-max/awesome-bio-agent-skills) into .agents/skills/jgi-lakehouse in your project. Codex loads it when a task matches its description.

Can I use Jgi Lakehouse 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 BioTender-max/awesome-bio-agent-skills --skill jgi-lakehouse -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/jgi-lakehouse, .gemini/skills/jgi-lakehouse, .github/skills/jgi-lakehouse and .opencode/skills/jgi-lakehouse in your project.

What does Jgi Lakehouse need to run?

Going by SKILL.md and its folder, Jgi Lakehouse needs the command-line tools its instructions call (rg, python3 and pip). Our summary lists: Docker.

Does Jgi Lakehouse access the network?

SKILL.md names 2 domains. In commands or code: lakehouse-1.jgi.lbl.gov and github.com; the agent is likely to contact these when it follows the instructions. This is read from the text; nothing was executed.

Is Jgi Lakehouse 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Jgi Lakehouse use?

Jgi Lakehouse has a licence file (the repository's licence) that doesn't match a standard licence. Read it on GitHub before reusing the skill.

How many tokens does Jgi Lakehouse use?

About 3.7k tokens (SKILL.md is roughly 15k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 315 tokens, read only when the agent opens those files.

What are the alternatives to Jgi Lakehouse?

Skills that share tags, products or a category with Jgi Lakehouse: Clickhouse Logs Queries (supabase/supabase, 111k stars), Chdb Datastore (vemetric/vemetric, 395 stars), Chdb SQL (vemetric/vemetric, 395 stars) and Biomarker Database Analysis (aws-samples/amazon-bedrock-agents-healthcare-lifesciences, 274 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Jgi Lakehouse?

BioTender-max (a GitHub user) maintains it in BioTender-max/awesome-bio-agent-skills, which has 200 GitHub stars. The repository holds 23 skills in this directory. The repository was last updated on July 1, 2026.

Source: BioTender-max/awesome-bio-agent-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.