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.
npx skills add jnPiyush/AgentX --skill databricksgit clone --depth 1 https://github.com/jnPiyush/AgentXWrote 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/skills/jnpiyush/agentx/databricks)<a href="https://agentmods.dev/skills/jnpiyush/agentx/databricks"><img src="https://agentmods.dev/badge/skills/jnpiyush/agentx/databricks/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.
<a href="https://agentmods.dev/skills/jnpiyush/agentx/databricks"><img src="https://agentmods.dev/badge/skills/jnpiyush/agentx/databricks.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high YARA Match · line 29 YARA rule matched a hack tool or exploit indicator (offensive tools, reconnaissance, privilege escalation, or exploit frameworks).Fix: Remove offensive tool references and exploit code. Legitimate agent skills should not contain penetration testing tools, exploit frameworks, or reconnaissance utilities.
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 | $0.00069 | $0.03533 |
| Opus 5.5 | $0.00028 | $0.01413 |
| Sonnet 5.5 | $0.00014 | $0.00707 |
| Haiku 4.5 | $0.00007 | $0.00353 |
Grade A, and why
databricks 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.
How it starts
The opening of the file, as written. The whole thing — 260 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Databricks
Unified Lakehouse platform combining Apache Spark, Delta Lake, MLflow, and Unity Catalog for data engineering, analytics, and AI/ML at scale.
When to Use
- Building Delta Lakehouses with medallion architecture (Bronze -> Silver -> Gold)
- Ingesting streaming or batch data with Auto Loader or Structured Streaming
- Creating DLT (Delta Live Tables) pipelines with built-in data quality
- Running ML experiments tracked in MLflow and serving models via Model Serving
- Governing data assets across clouds with Unity Catalog
- Deploying reproducible jobs and pipelines with Databricks Asset Bundles
- Running SQL analytics on Delta tables via Databricks SQL Warehouses
- Building AI/ML features with Vector Search and Feature Engineering
Decision Tree
Working with Databricks?
+-- Need storage layer?
| +-- Semi-structured / schema-on-read / ML data -> Delta Lakehouse
| +-- Need ACID + time travel -> Delta Lake tables
| +-- Need governance across workspace -> Unity Catalog
+-- Need ingestion?
| +-- Cloud files (S3/ADLS/GCS) incremental -> Auto Loader
| +-- Kafka/Kinesis/Event Hubs streaming -> Structured Streaming
| +-- One-time bulk load -> COPY INTO or Spark batch
+-- Need pipelines?
| +-- Declarative, built-in quality checks -> Delta Live Tables (DLT)
| +-- Imperative DAG with custom logic -> Databricks Workflows
| +-- Simple notebook job -> Workflow single-task job
+-- Need ML/AI?
| +-- Experiment tracking -> MLflow Tracking
| +-- Model registry + governance -> MLflow Registry (UC-backed)
| +-- Real-time inference -> Model Serving endpoints
| +-- Semantic / vector similarity search -> Databricks Vector Search
+-- Need IaC / CI-CD?
-> Databricks Asset Bundles (DABs)
Core Concepts
Lakehouse Architecture
Databricks combines the best of data warehouses and data lakes:
What ships with it
13 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- assets/databricks.yml 97 B
- assets/dlt_pipeline.py 169 B runs code
- assets/medallion_bronze.py 166 B runs code
- assets/medallion_silver.py 172 B runs code
- assets/mlflow_training.py 150 B runs code
- references/dab-templates.md 1.8 KB
- references/delta-lake-operations.md 2.0 KB
- references/dlt-guide.md 2.4 KB
- references/mlflow-guide.md 2.0 KB
- references/streaming-ingestion.md 2.1 KB
- references/unity-catalog.md 2.3 KB
- references/vector-search-and-compute.md 2.1 KB
- references/workflows-and-sql.md 2.4 KB
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.
- 1mo ago Changed f813fd17159b
- 1mo ago First seen · 260 lines · 69 tokens per session scan A 51bfaad7145c
databricks is a skill published in the GitHub repository jnPiyush/AgentX (16 stars, last pushed 3d ago), licensed Apache-2.0. It adds 69 tokens to every session and 3,533 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 2026-09-03.
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