Token导航 LogoToken导航

Agent Skill · 研究检索

jgi-lakehouse(杰吉莱克豪斯)

jgi-lakehouse 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

jgi-lakehouse 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,674 个 Skill 里排第 60,488。

总安装 367周安装 15GitHub Stars 1下载 119核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:jgi-lakehouse(杰吉莱克豪斯)
来源仓库:https://github.com/fmschulz/omics-skills
仓库路径:skills/jgi-lakehouse
安装命令:
npx skills add https://github.com/fmschulz/omics-skills --skill jgi-lakehouse
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/fmschulz/omics-skills --skill jgi-lakehouse

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

jgi-lakehouse 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。适用于基因组学或生物信息学相关数据湖资源查询。通过 npx skills add 命令从 GitHub 仓库安装并使用。

安装前建议确认权限范围和维护状态,避免触发联网或文件读写操作。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/jgi-lakehouse

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/fmschulz/omics-skills --skill jgi-lakehouse;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

jgi-lakehouse 怎么安装?

在终端执行 npx skills add https://github.com/fmschulz/omics-skills --skill jgi-lakehouse。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

jgi-lakehouse 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

jgi-lakehouse 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

jgi-lakehouse 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

jgi-lakehouse 用的人多吗?

公开数据是累计安装 367 次,近一周安装 15 次,下载 119 次,GitHub 1 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

jgi-lakehouse 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
jgi-lakehouse

杰吉莱克豪斯 · 本页

3671需要联网未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

JGI Lakehouse Skill

Instructions

  1. Decide whether the task needs metadata from the Lakehouse or files from the JGI filesystem.
  2. Start with a small validation query, then remove LIMIT for final counts or complete result sets.
  3. Use the query and download patterns below instead of improvising SQL or filesystem paths.
  4. Record the exact tables, filters, taxon OIDs, file paths, and commands used.

Quick Reference

TaskAction
Find metadataQuery the Lakehouse with SQL
Download IMG genome packagesCopy {taxon_oid}.tar.gz from /clusterfs/jgi/img_merfs-ro/img_web/img_web_data/download/
Retrieve Mycocosm or Phytozome filesQuery portal.downloadRequestFiles, then copy from /global/dna/dm_archive/
Query metagenome proteinsUse the NUMG tables and join on both oid and gene_oid
Inspect schemasUse SHOW TABLES and DESCRIBE before writing larger joins

Input Requirements

  • Clear task description: metadata discovery, annotation lookup, file retrieval, or sequence download
  • Access to the relevant JGI environment and filesystem paths
  • Known identifiers when available: GOLD IDs, IMG taxon OIDs, project names, or organism names
  • Output scope: exploratory sample, complete count, or file retrieval target

Output

  • SQL queries or filesystem commands that match the request
  • Returned metadata, counts, taxon IDs, file paths, or copied files
  • A concise summary of what was found, including any limits or caveats

Quality Gates

  • Data source chosen correctly: Lakehouse for metadata, filesystem for sequence files
  • LIMIT removed from final comprehensive queries
  • Table and column names validated before final query execution
  • File paths and taxon OIDs recorded exactly

Examples

See the worked examples and query blocks below, especially:

  • ## NUMG (Metagenome Proteins) Agent Workflow
  • ## Downloading Genomes with IMG Taxon OIDs
  • ## Portal Downloads (Mycocosm / Phytozome)
  • ## Common Queries

Troubleshooting

Issue: Query returns only a sample and not the full answer Solution: Remove LIMIT after validating query shape and use aggregation for totals.

Issue: Expected genome sequences are not in the Lakehouse Solution: Use the filesystem paths described below; the Lakehouse is for metadata and annotations.

Quick Start

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

Two data access methods:

  1. Lakehouse (Dremio) → Metadata, annotations, taxonomy (no sequences)
  2. JGI Filesystem → Actual genome files (FNA, FAA, GFF) via taxon OID

SQL Dialect: ANSI SQL (not PostgreSQL)

  • Use CAST(x AS type) not ::
  • Use REGEXP_LIKE() not ~
  • Identifiers with dashes need double quotes: "gold-db-2 postgresql"
-- Quick test
SELECT gold_id, project_name FROM "gold-db-2 postgresql".gold.project
WHERE is_public = 'Yes' LIMIT 5;

When to Use

  • Query JGI genomics metadata (GOLD, IMG, Mycocosm, Phytozome)
  • Find genomes and/or metagenomes by taxonomy, ecosystem, or phenotype.
  • Download microbial genomes with IMG taxon OIDs
  • Cross-reference GOLD projects with IMG annotations

Data Access: Lakehouse vs Filesystem

NeedSourceAccess Method
Metadata (taxonomy, projects)LakehouseSQL via REST API
Gene annotations (COG, Pfam, KO)LakehouseSQL via REST API
Genome sequences (FNA)JGI FilesystemCopy from /clusterfs/jgi/img_merfs-ro/
Protein sequences (FAA)JGI FilesystemCopy from /clusterfs/jgi/img_merfs-ro/
Metagenome proteins onlyLakehousenumg-iceberg.faa table

Critical insight: The Lakehouse is a METADATA warehouse. Genome sequences must be accessed from the JGI filesystem.


Key Data Sources

SourcePathContents
GOLD"gold-db-2 postgresql".gold.*Projects, studies, samples, taxonomy
IMG"img-db-2 postgresql".img_core_v400.*Taxons, genes, annotations (244 tables)
Portal"portal-db-1".portal.*Download tracking, file paths
Mycocosm"myco-db-1 mysql".<organism>.*Fungal genomes (2,711 schemas)
Phytozome"plant-db-7 postgresql".*Plant genomics
NUMG"numg-iceberg"."numg-iceberg".*Metagenome proteins, Pfam hits

Full table catalog: See docs/data-catalog.md


NUMG (Metagenome Proteins) Agent Workflow

Use NUMG when the task is metagenome protein sequence/domain analysis.

Scope rules:

  • numg-iceberg is metagenome-focused.
  • Do not use NUMG for isolate genome protein retrieval; use IMG filesystem packages.

Core tables:

  • "numg-iceberg"."numg-iceberg".faa

- oid, gene_oid, faa (protein sequence)

  • "numg-iceberg"."numg-iceberg".gene2pfam

- oid, gene_oid, pfam, evalue, alignment coordinate fields

Recommended query flow:

-- 1) Confirm available NUMG tables
SHOW TABLES IN "numg-iceberg"."numg-iceberg";

-- 2) Inspect schema before writing joins/filters
DESCRIBE "numg-iceberg"."numg-iceberg".faa;
DESCRIBE "numg-iceberg"."numg-iceberg".gene2pfam;

-- 3) Domain filter (use exact lowercase pfam IDs)
SELECT oid, gene_oid, pfam, evalue
FROM "numg-iceberg"."numg-iceberg".gene2pfam
WHERE pfam IN ('pfam00001', 'pfam00004')
LIMIT 100;

-- 4) Join domains to protein sequences
SELECT
  p.oid,
  p.gene_oid,
  p.pfam,
  p.evalue,
  f.faa
FROM "numg-iceberg"."numg-iceberg".gene2pfam p
JOIN "numg-iceberg"."numg-iceberg".faa f
  ON p.oid = f.oid
 AND p.gene_oid = f.gene_oid
WHERE p.pfam = 'pfam00001'
LIMIT 100;

Important NUMG rules:

  • Join on both oid and gene_oid (not gene_oid alone).
  • Keep Pfam filters exact (pfam00001, not case-transformed).
  • Always start with LIMIT and expand only after verifying row shape.

See also: examples/05-query-numg-metagenome-proteins.md


Downloading Genomes with IMG Taxon OIDs

Option 1: JGI Filesystem (Fastest)

# Genome packages are at:
/clusterfs/jgi/img_merfs-ro/img_web/img_web_data/download/{taxon_oid}.tar.gz

# Example: Copy and extract
cp /clusterfs/jgi/img_merfs-ro/img_web/img_web_data/download/8136918376.tar.gz .
tar -xzf 8136918376.tar.gz

Package contents:

  • {taxon_oid}.fna - Genome assembly
  • {taxon_oid}.genes.faa - Protein sequences
  • {taxon_oid}.genes.fna - Gene nucleotide sequences
  • {taxon_oid}.gff - GFF annotations
  • {taxon_oid}.cog.tab.txt - COG annotations
  • {taxon_oid}.pfam.tab.txt - Pfam annotations
  • {taxon_oid}.ko.tab.txt - KEGG KO annotations

Portal Downloads (Mycocosm / Phytozome)

The portal tracks downloadable files for Mycocosm and Phytozome in "portal-db-1".portal.downloadRequestFiles. Use filePath to copy data from the JGI filesystem (/global/dna/dm_archive/...).

Mycocosm (fungal genomes/proteins):

SELECT filePath, fileType
FROM "portal-db-1".portal.downloadRequestFiles
WHERE LOWER(filePath) LIKE '%mycocosm%'
  AND (filePath LIKE '%.fasta%' OR filePath LIKE '%.fa%' OR filePath LIKE '%.faa%')
LIMIT 20;

Phytozome (plant genomes/proteins):

SELECT filePath, fileType
FROM "portal-db-1".portal.downloadRequestFiles
WHERE LOWER(filePath) LIKE '%phytozome%'
  AND (filePath LIKE '%.fa%' OR filePath LIKE '%.fna%' OR filePath LIKE '%.faa%')
LIMIT 20;

Download from filesystem:

cp /global/dna/dm_archive/<path/from-filePath> .

Notes:

  • fileType typically includes Assembly, Annotation, or Sequence.
  • virtualPath can provide a user-facing download label but filePath is the real location.

Query Best Practices

⚠️ CRITICAL: When building queries, distinguish between exploration and comprehensive analysis:

Exploration Queries

Use LIMIT for quick validation during development:

-- For testing query structure and results
SELECT gold_id, project_name
FROM "gold-db-2 postgresql".gold.project
WHERE is_public = 'Yes'
LIMIT 10;  -- ✓ OK for testing

Comprehensive Queries

Remove LIMIT and other result-limiting clauses when answering actual questions:

-- For getting actual dataset counts/results
SELECT COUNT(DISTINCT taxon_oid)
FROM "img-db-2 postgresql".img_core_v400.taxon
WHERE genome_type = 'metagenome'
  AND is_public = 'Yes';
-- ✓ No LIMIT - gets true total

Common pitfalls:

  • ❌ LIMIT 100 on initial exploration → assumes only 100 results exist
  • ❌ LIMIT 50 on a "find all" query → misses 99% of data
  • ❌ Using FETCH FIRST N ROWS → same issue as LIMIT

Best practice:

  1. Use LIMIT with COUNT(*) or small LIMIT during development
  2. Once query logic is correct, remove LIMIT to get true results
  3. For very large result sets, use aggregation (COUNT, GROUP BY) to summarize instead

Common Queries

Find Bacterial Isolate Genomes

-- Get count of all finished bacterial isolates
SELECT COUNT(DISTINCT taxon_oid) as total_isolates
FROM "img-db-2 postgresql".img_core_v400.taxon
WHERE domain = 'Bacteria'
  AND genome_type = 'isolate'
  AND is_public = 'Yes'
  AND seq_status = 'Finished';

-- Get sample of isolates (if you need details)
SELECT taxon_oid, taxon_display_name, phylum, genus, species
FROM "img-db-2 postgresql".img_core_v400.taxon
WHERE domain = 'Bacteria'
  AND genome_type = 'isolate'
  AND is_public = 'Yes'
  AND seq_status = 'Finished'
LIMIT 100;

Link GOLD Project to IMG Taxon

SELECT COUNT(DISTINCT t.taxon_oid) as total_linked
FROM "img-db-2 postgresql".img_core_v400.taxon t
WHERE t.sequencing_gold_id IS NOT NULL;

Find Genomes with File Paths (Portal)

SELECT COUNT(DISTINCT taxonOid) as total_tar_gz
FROM "portal-db-1".portal.downloadRequestFiles
WHERE taxonOid IS NOT NULL
  AND filePath LIKE '%.tar.gz';

Critical Pitfalls

WrongCorrect
Using LIMIT in comprehensive queriesRemove LIMIT when answering actual questions; use COUNT() for aggregation
Join ncbi_assembly on project_idncbi_assembly has no project_id; use bioproject or biosample
project.ecosystemJoin study via master_study_id
SHOW SCHEMAS IN "source"Works, but some syntax errors in older Dremio
Get sequences from LakehouseDownload from JGI filesystem
sra_experiment_v2.platformUse library_instrument
gene_ko_terms = 'K00025'Use gene_ko_terms = 'KO:K00025'
Join NUMG on gene_oid onlyJoin on both oid and gene_oid
Case-normalizing large function tablesUse exact normalized values (pfam00001, COG1389, etc.)
Isolate benchmark counts varyAdd obsolete_flag = 'No' and is_public = 'Yes'
IMG.gene_feature fails expansionFallback to "img-db-2 postgresql".img_core_v400.* tables
show_schemas() misses sourcesUse higher limit (e.g. show_schemas(limit=2000))

Authentication

export DREMIO_PAT=$(cat ~/.secrets/dremio_pat)

Token setup: See docs/authentication.md


API Access

REST API Base: http://lakehouse-1.jgi.lbl.gov:9047/api/v3

# Use scripts/rest_client.py
from rest_client import query
results = query("SELECT * FROM ... LIMIT 10")

Arrow Flight (Python)

For higher-performance programmatic access, use Arrow Flight with Python.

python3 -m venv venv
. venv/bin/activate
pip install \
  https://github.com/dremio-hub/arrow-flight-client-examples/releases/download/dremio-flight-python-v1.1.0/dremio_flight-1.1.0-py3-none-any.whl

Full guide: docs/arrow-flight-python.md


Documentation

平台分布

Codex

33.63%
按下载量换算40

Claude

30.41%
按下载量换算36

Cursor

18.85%
按下载量换算22

Gemini CLI

9.72%
按下载量换算12

安全审计

Gen Agent Trust Hub

可疑

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

继续浏览同类 Skills