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 fabric-analyticsgit 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/fabric-analytics)<a href="https://agentmods.dev/skills/jnpiyush/agentx/fabric-analytics"><img src="https://agentmods.dev/badge/skills/jnpiyush/agentx/fabric-analytics/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/fabric-analytics"><img src="https://agentmods.dev/badge/skills/jnpiyush/agentx/fabric-analytics.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00055 | $0.02846 |
| Opus 5.5 | $0.00022 | $0.01138 |
| Sonnet 5.5 | $0.00011 | $0.00569 |
| Haiku 4.5 | $0.00006 | $0.00285 |
Grade A, and why
fabric-analytics 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 — 314 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Fabric Analytics
Unified analytics platform on OneLake - data engineering, warehousing, notebooks, pipelines, and semantic models.
When to Use
- Building data lakehouses with medallion architecture (Bronze -> Silver -> Gold)
- Creating or querying Fabric Warehouses with T-SQL
- Developing PySpark notebooks for data transformation
- Orchestrating ETL/ELT with data pipelines
- Building semantic models for Power BI (DirectLake mode)
- Querying data via SQL endpoints or DAX
Decision Tree
Working with Microsoft Fabric?
+- Need storage layer?
| +- Semi-structured / schema evolution -> Lakehouse
| +- Full T-SQL / stored procs / DML -> Warehouse
| - Unsure -> Start with Lakehouse (more flexible)
+- Need data transformation?
| +- Simple data copy -> Pipeline Copy Activity
| +- Light transforms (300+ built-in) -> Dataflow Gen2
| - Complex logic / ML / custom code -> Spark Notebook
+- Need orchestration?
| - Pipeline with activities + dependencies
+- Need reporting layer?
| - Semantic Model with DirectLake mode
- Need conversational analytics?
- See: fabric-data-agent skill
Core Concepts
OneLake & Delta Format
All Fabric workloads share OneLake - a single logical data lake built on Delta format:
| Principle | Details |
|---|---|
| Single copy | No data silos - all items reference the same storage |
| Delta format | ACID transactions, time travel, schema evolution |
| Open format | Parquet-based, readable by any Spark engine |
| Shortcuts | Reference external storage (ADLS, S3) without copying |
Medallion Architecture
| Layer | Purpose | Example Tables | Format |
|---|---|---|---|
| Bronze | Raw ingestion, as-is from source | raw_orders, raw_customers |
Delta (append-only) |
| Silver | Cleaned, deduplicated, typed | clean_orders, clean_customers |
Delta (merge/upsert) |
| Gold | Business-ready aggregates | fact_sales, dim_product |
Delta (star schema) |
What ships with it
6 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.
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 c3c05eb52d7c
- 1mo ago First seen · 314 lines · 55 tokens per session scan A d2c1e9d02880
fabric-analytics is a skill published in the GitHub repository jnPiyush/AgentX (16 stars, last pushed 3d ago), licensed Apache-2.0. It adds 55 tokens to every session and 2,846 once invoked, about $0.0002 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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