What is watsonxdata-lakehouse?

A guide for configuring IBM watsonx.data, a cloud service for combining data from object storage and databases in one queryable lakehouse. It covers Apache Iceberg tables, Presto SQL queries, and Apache Spark processing.

Use it to register IBM Cloud Object Storage or AWS S3 buckets, connect Db2, PostgreSQL, or MySQL, link catalogs to Presto, configure Spark, create schemas, and run federated SQL queries.

It provides scripts and instructions for connecting storage, databases, authentication, and query engines without manually piecing together the setup.

watsonxdata-lakehouse — Skill by ibm-self-serve-assets/building-blocks

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.

Any agent

npx skills add ibm-self-serve-assets/building-blocks --skill watsonxdata-lakehouse

Clone the repo

git clone --depth 1 https://github.com/ibm-self-serve-assets/building-blocks

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/ibm-self-serve-assets/building-blocks/watsonxdata-lakehouse/github.svg)](https://agentmods.dev/skills/ibm-self-serve-assets/building-blocks/watsonxdata-lakehouse)

Your own site

<a href="https://agentmods.dev/skills/ibm-self-serve-assets/building-blocks/watsonxdata-lakehouse"><img src="https://agentmods.dev/badge/skills/ibm-self-serve-assets/building-blocks/watsonxdata-lakehouse/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/ibm-self-serve-assets/building-blocks/watsonxdata-lakehouse"><img src="https://agentmods.dev/badge/skills/ibm-self-serve-assets/building-blocks/watsonxdata-lakehouse.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 88 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,595 The whole file, excluding the scripts and references it only reads on demand.

Security scan B 2 findings. A grade says what 26 rules found in the file — not that it is safe.

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.

Model	Per session	Once invoked
Fable 5.1	$0.00088	$0.01595
Opus 5.5	$0.00035	$0.00638
Sonnet 5.5	$0.00018	$0.00319
Haiku 4.5	$0.00009	$0.00160

Measured 2mo ago against content hash 9751f3252a8e, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade B, and why

watsonxdata-lakehouse scanned grade B with 2 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 2mo ago.

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.

Sends data to an external URLmediumData exfiltration

A POST to an outside endpoint may be telemetry or may be exfiltration; either way the mod talks to somewhere, and you should know where.

resp = requests.post("https://iam.cloud.ibm.com/identity/token",

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

resp = requests.post("https://iam.cloud.ibm.com/identity/token",

ibm-bob/skills/watsonxdata-lakehouse/SKILL.md · 175 lines

How it starts

The opening of the file, as written. The whole thing — 175 lines — stays where its author put it; the contents beside it link to each section on GitHub.

IBM watsonx.data Zero-Copy Lakehouse Builder

Purpose

Expert guidance for configuring IBM watsonx.data as a zero-copy lakehouse — registering storage buckets, connecting databases, associating catalogs with Presto engines, and running federated SQL queries — all via the watsonx.data REST API v2.

IBM Cloud Product Coverage

IBM Cloud Product	Usage
IBM watsonx.data	REST API v2: /bucket_registrations, /presto_engines, /catalogs, /database_registrations
IBM Cloud IAM	POST /identity/token (apikey grant) — with auto-refresh
IBM Cloud Object Storage	Registered as managed bucket in watsonx.data
IBM Db2	Registered as external database connection
Apache Iceberg	Table format for open lakehouse storage
Apache Spark	Heavy ETL jobs on Iceberg tables
Presto	Interactive federated SQL queries

Objective

Generate production-ready Python 3.12 scripts that:

Authenticate to IBM Cloud via IAMTokenManager (5-minute buffer refresh)
Register IBM COS, AWS S3, and other buckets as watsonx.data storage
Connect Db2, PostgreSQL, MySQL databases to watsonx.data
Associate catalogs with Presto engines for federated queries
Create Iceberg schemas and tables
Follow the existing watsonxdata_setup.py patterns exactly

Rules

Base URL pattern: https://{region}.lakehouse.cloud.ibm.com/lakehouse/api/v2
Always build headers with {"Authorization": "Bearer {token}", "AuthInstanceId": AUTH_INSTANCE_ID, "Content-Type": "application/json"}
The AuthInstanceId is the watsonx.data CRN (from config)
Use wait_with_progress(seconds) for delays between API operations
All resource registrations are synchronous — allow 30–90 second waits for catalog propagation
Supported regions: us-south, eu-de, au-syd, jp-tok

Scope

IBM watsonx.data instance configuration and bucket registration
IBM COS, AWS S3, Azure ADLS bucket registration
IBM Db2, PostgreSQL, MySQL database connections
Presto engine catalog association
Apache Iceberg schema and table creation via Presto SQL
Apache Spark job configuration for Iceberg ETL
Federated query patterns across heterogeneous sources

Read the full file on GitHub · 175 lines

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.

2mo ago First seen · 175 lines · 88 tokens per session scan B 9751f3252a8e

Subscribe to this mod's changes

watsonxdata-lakehouse is a skill published in the GitHub repository ibm-self-serve-assets/building-blocks (28 stars, last pushed yesterday), licensed Apache-2.0. It adds 88 tokens to every session and 1,595 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it B with 2 findings (sends data to an external url, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Cloud Databases DevOps and cloud

watsonxdata-lakehouse next to 6 skills from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
watsonxdata-lakehouseibm-self-serve-assets/building-blocks	Skill	28	yesterday	Apache-2.0	B	88	Claude Code, Codex
cloud-databases-onboardinggoogle/skills	Skill	22k	yesterday	Apache-2.0	A	83	Claude Code, Codex
atlas-lakebaseariga/atlas	Skill	8.8k	yesterday	Apache-2.0	A	140	Claude Code
azure-mgmt-mongodbatlas-dotnetmicrosoft/skills	Skill	3.2k	yesterday	MIT	A	64	Claude Code
azure-resource-manager-mysql-dotnetmicrosoft/skills	Skill	3.2k	yesterday	MIT	A	87	Claude Code
azure-resource-manager-redis-dotnetmicrosoft/skills	Skill	3.2k	yesterday	MIT	A	114	Claude Code
azure-resource-manager-sql-dotnetmicrosoft/skills	Skill	3.2k	yesterday	MIT	A	109	Claude Code

watsonxdata-lakehouse