Microsoft Fabric Skills is a collection of reusable instructions and MCP systems that help AI assistants work with Microsoft Fabric workloads, APIs, queries, and operations. It is intended for users of GitHub Copilot CLI and compatible coding tools; the catalogue entries are the skills, agents, instructions, MCP systems, plugins, and rules distributed by the project.
Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add microsoft/skills-for-fabric/plugin install fabric-skillsWrote 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/microsoft/skills-for-fabric/e2e-medallion-architecture)<a href="https://agentmods.dev/skills/microsoft/skills-for-fabric/e2e-medallion-architecture"><img src="https://agentmods.dev/badge/skills/microsoft/skills-for-fabric/e2e-medallion-architecture/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/microsoft/skills-for-fabric/e2e-medallion-architecture"><img src="https://agentmods.dev/badge/skills/microsoft/skills-for-fabric/e2e-medallion-architecture.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00090 | $0.05995 |
| Opus 5 | $0.00045 | $0.02998 |
| Sonnet 5 | $0.00018 | $0.01199 |
| Haiku 4.5 | $0.00009 | $0.00600 |
Grade A, and why
e2e-medallion-architecture scanned grade A with 1 finding 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 12d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- Reading from **external HTTP/HTTPS URLs** directly in Spark — Fabric Spark cannot access arbitrary external URLs; land data in lakehouse `Files/` first (via `curl`, OneLake API, or Fabric pipeline Copy activity), then How it starts
The opening of the file, as written. The whole thing — 362 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Telemetry — MANDATORY. Every
api.fabric.microsoft.comcall must carryx-ms-fabric-skill: e2e-medallion-architecture(az rest:--headers "x-ms-fabric-skill=e2e-medallion-architecture"), including every LRO poll,fabric_lroand retry. Snippets omit it — add it anyway.
CRITICAL NOTES
- To find the workspace details (including its ID) from workspace name: list all workspaces and, then, use JMESPath filtering
- To find the item details (including its ID) from workspace ID, item type, and item name: list all items of that type in that workspace and, then, use JMESPath filtering
End-to-End Medallion Architecture
Prerequisite Knowledge
Read these companion documents — they contain the foundational context this skill depends on:
- COMMON-CORE.md — Fabric REST API patterns, authentication, token audiences, item discovery
- COMMON-CLI.md —
az rest,az login, token acquisition, Fabric REST via CLI - SPARK-AUTHORING-CORE.md — Notebook deployment, lakehouse creation, job execution
- notebook-api-operations.md — Required for notebook creation —
.ipynbstructure requirements, cell format,getDefinition/updateDefinitionworkflow
For Spark-specific optimization details, see data-engineering-patterns.md.
Architecture Overview
Medallion Architecture is a data lakehouse pattern with three progressive layers:
| Layer | Purpose | Optimization Profile | Use Case |
|---|---|---|---|
| Bronze (Raw) | Land raw data exactly as received | Write-optimized, append-only, partitioned by ingestion date | Audit trail, reprocessing, lineage |
| Silver (Cleaned) | Deduplicated, validated, conformed data | Balanced read/write, partitioned by business date | Feature engineering, operational reporting |
| Gold (Aggregated) | Pre-calculated metrics for analytics | Read-optimized (ZORDER, compaction), partitioned by month/year | Power BI reports, dashboards, ad-hoc analytics via SQL endpoint |
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.
- 12d ago First seen · 362 lines · 90 tokens per session scan A 512f843d21ba
e2e-medallion-architecture is a skill published in the GitHub repository microsoft/skills-for-fabric (1,140 stars, last pushed yesterday), licensed MIT. It adds 90 tokens to every session and 5,995 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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