databricks-ml-pipeline

databricks-ml-pipeline is a skill for Claude Code from databricks-solutions/databricks-exec-code-mcp. It costs 64 tokens per session (4,520 once invoked), scanned A, original, no licence file.

A set of machine-learning workflows that run on Databricks, a platform for working with data and models. It covers preparing data, training models, tracking experiments, registering models, and deploying pipelines.

In plain words
What is it for?
Use it to explore data, create features, tune and train models, track work with MLflow, register models in Unity Catalog, and deploy Databricks Asset Bundles.
Why use it?
It brings the main steps of developing and running a machine-learning model into one workflow. It also helps track model experiments and manage registered models.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: model in frontmatter.

Good fit Use it to explore data, create features, tune and train models, track work with MLflow, register models in Unity Catalog, and deploy Databricks Asset Bundles.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/databricks-solutions/databricks-exec-code-mcp/databricks-ml-pipeline
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 databricks-solutions/databricks-exec-code-mcp --skill databricks-ml-pipeline
Clone the repo
git clone --depth 1 https://github.com/databricks-solutions/databricks-exec-code-mcp

Made for: Claude Code.

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.

agentmods badge for databricks-ml-pipeline

README.md
[![agentmods](https://agentmods.dev/badge/skills/databricks-solutions/databricks-exec-code-mcp/databricks-ml-pipeline/github.svg)](https://agentmods.dev/skills/databricks-solutions/databricks-exec-code-mcp/databricks-ml-pipeline)
Your own site
<a href="https://agentmods.dev/skills/databricks-solutions/databricks-exec-code-mcp/databricks-ml-pipeline"><img src="https://agentmods.dev/badge/skills/databricks-solutions/databricks-exec-code-mcp/databricks-ml-pipeline/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.

agentmods 80×15 button for databricks-ml-pipeline

Your own site · 80×15
<a href="https://agentmods.dev/skills/databricks-solutions/databricks-exec-code-mcp/databricks-ml-pipeline"><img src="https://agentmods.dev/badge/skills/databricks-solutions/databricks-exec-code-mcp/databricks-ml-pipeline.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 64 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,520 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin unknown 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00064 $0.04520
Opus 5.5 $0.00026 $0.01808
Sonnet 5.5 $0.00013 $0.00904
Haiku 4.5 $0.00006 $0.00452

Measured 1mo ago against content hash 8efa024590c4, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

databricks-ml-pipeline scanned grade A with 0 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 1mo 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.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/databricks-ml-pipeline/SKILL.md · 685 lines

The source is not reproduced here

A licence we could not identify

The repository carries a LICENSE file, but it is custom or dual enough that GitHub cannot name it and neither can this catalogue. Unknown terms are not permission, so the body is not copied here. Read the licence at the source and decide for yourself.

Read it on GitHub

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.

  1. 1mo ago First seen · 685 lines · 64 tokens per session scan A 8efa024590c4

Subscribe to this mod's changes

databricks-ml-pipeline is a skill published in the GitHub repository databricks-solutions/databricks-exec-code-mcp (14 stars, last pushed 8mo ago), with no licence file. It adds 64 tokens to every session and 4,520 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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