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.
git clone --depth 1 https://github.com/revodatanl/databricks-mcp-serverWrote 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.
[](https://agentmods.dev/rules/revodatanl/databricks-mcp-server/dab-pipeline-config)<a href="https://agentmods.dev/rules/revodatanl/databricks-mcp-server/dab-pipeline-config"><img src="https://agentmods.dev/badge/rules/revodatanl/databricks-mcp-server/dab-pipeline-config.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00019 | $0.00214 |
| Opus 5 | $0.00010 | $0.00107 |
| Sonnet 5 | $0.00004 | $0.00043 |
| Haiku 4.5 | $0.00002 | $0.00021 |
Grade A, and why
dab-pipeline-config 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 7d 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.
What it actually says
Databricks Jobs vs Pipelines
When to Use Jobs
- Use a Job for general workflows: data processing, ML training, ETL, scheduled tasks, and multi-step workflows.
- "Run a notebook on schedule" → Use a Job
- "Multiple steps with dependencies" → Use a Job with multiple tasks
When to Use Pipelines
- Use a Pipeline (Delta Live Tables, DLT) for streaming data, data quality enforcement, and declarative ETL.
- "Process streaming data with DLT" → Use a Pipeline
- "Need data quality checks and auto-recovery" → Use a Pipeline
File Organization
-
Organize files as follows:
resources/ ├── jobs/ # Scheduled workflows, ML training └── pipelines/ # DLT streaming/batch processing
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.
- 7d ago First seen · 29 lines · 19 tokens per session scan A 4f0a41079a5b
dab-pipeline-config is a cursor rule published in the GitHub repository revodatanl/databricks-mcp-server (7 stars, last pushed 1mo ago), licensed MIT. It adds 19 tokens to every session and 214 once invoked, about $0.0001 per session on Opus 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 2026-08-31.
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