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
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 microsoft/skills-for-fabric --skill spark-cligit clone --depth 1 https://github.com/microsoft/skills-for-fabricWrote 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/spark-cli)<a href="https://agentmods.dev/skills/microsoft/skills-for-fabric/spark-cli"><img src="https://agentmods.dev/badge/skills/microsoft/skills-for-fabric/spark-cli.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 | $0.00094 | $0.02380 |
| Opus 5 | $0.00047 | $0.01190 |
| Sonnet 5 | $0.00019 | $0.00476 |
| Haiku 4.5 | $0.00009 | $0.00238 |
Grade A, and why
spark-cli 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.
How it starts
The opening of the file, as written. The whole thing — 102 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: spark-cli(az rest:--headers "x-ms-fabric-skill=spark-cli"), 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
- Skill disambiguation: use
spark-clifor notebook cell code (including%%sqlcells), named notebook runs, Livy sessions, Spark failure triage, and everything about a Materialized Lake View -- writing the definition, reviewing a query for incremental-refresh readiness, and scheduling, refreshing, monitoring or diagnosing an existing one. A KQL materialized view in an Eventhouse iseventhouse-cli; plain read-only T-SQL against a Warehouse or Lakehouse SQL endpoint issqldw-cli.- Hard routing boundary: never execute an Eventhouse/KQL materialized-view request from this skill. Route it to
eventhouse-cli; if that skill is unavailable, state that the request cannot be completed in the current skill context and stop without calling Fabric APIs or creating artifacts.
Fabric Spark and Materialized Lake Views -- CLI Skill
This one skill owns Fabric Spark: notebook cell authoring, notebook runs, Livy-session analysis, Spark failure diagnostics, and the whole Materialized Lake View lifecycle.
It is a mode dispatcher and contains NO procedures. Pick the mode that matches the request from the table below, then read the matching references/<mode>.md file end to end with your file-reading tool BEFORE issuing a single command. That file holds the endpoints, payload shapes, templates and gotchas; acting without it produces wrong payloads and wrong results.
Mode selection
What ships with it
18 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.
- references/authoring.md 33 KB
- references/authoring/resources/data-engineering-patterns.md 24 KB
- references/authoring/resources/development-workflow.md 7.4 KB
- references/authoring/resources/infrastructure-orchestration.md 10 KB
- references/authoring/resources/materialized-lake-view-patterns.md 20 KB
- references/authoring/resources/mlv-incremental-refresh-patterns.md 11 KB
- references/authoring/resources/notebook-api-operations.md 14 KB
- references/consumption.md 12 KB
- references/mlv.md 33 KB
- references/operations.md 20 KB
- references/operations/automated-diagnostic-workflow.md 13 KB
- references/operations/diagnostic-workflow.md 7.3 KB
- references/operations/job-diagnostics.md 18 KB
- references/operations/jobinsight-api.md 7.2 KB
- references/operations/performance-patterns.md 17 KB
- references/operations/pipeline-diagnosis.md 21 KB
- references/operations/session-health.md 8.7 KB
- references/operations/spark-history-server.md 6.5 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.
- 7d ago First seen · 102 lines · 94 tokens per session scan A 3f620dc0a7b9
spark-cli is a skill published in the GitHub repository microsoft/skills-for-fabric (1,111 stars, last pushed 2d ago), licensed MIT. It adds 94 tokens to every session and 2,380 once invoked, about $0.0005 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 2026-08-30.
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