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 PatrickGallucci/fabric-skills --skill fabric-performance-monitoringgit clone --depth 1 https://github.com/PatrickGallucci/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/patrickgallucci/fabric-skills/fabric-performance-monitoring)<a href="https://agentmods.dev/skills/patrickgallucci/fabric-skills/fabric-performance-monitoring"><img src="https://agentmods.dev/badge/skills/patrickgallucci/fabric-skills/fabric-performance-monitoring/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/patrickgallucci/fabric-skills/fabric-performance-monitoring"><img src="https://agentmods.dev/badge/skills/patrickgallucci/fabric-skills/fabric-performance-monitoring.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 | $0.01282 |
| Opus 5 | $0.00045 | $0.00641 |
| Sonnet 5 | $0.00018 | $0.00256 |
| Haiku 4.5 | $0.00009 | $0.00128 |
Grade A, and why
fabric-performance-monitoring 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 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.
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 — 118 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Microsoft Fabric Performance Monitoring
Toolkit for monitoring, diagnosing, and optimizing Microsoft Fabric capacity and workload performance across Spark, Data Warehouse, Lakehouse, and Pipeline workloads.
When to Use This Skill
- Checking Fabric capacity utilization or CU consumption
- Diagnosing throttling errors (HTTP 430 / TooManyRequestsForCapacity)
- Monitoring Spark VCore usage and concurrency limits
- Querying Fabric REST APIs for capacity and workspace health
- Generating capacity performance reports
- Tuning Spark resource profiles (readHeavy, writeHeavy, balanced)
- Investigating job failures in the Monitoring Hub
- Analyzing autoscale billing vs capacity-based billing
- Reviewing background vs interactive operation patterns
- Planning capacity SKU sizing or rightsizing
Prerequisites
- PowerShell 7+ with Az.Fabric module installed
- Microsoft Entra ID app registration with Fabric API permissions
- Fabric Capacity Admin or Workspace Admin role
- Fabric Capacity Metrics app installed (for visual monitoring)
Core Concepts
Capacity Units and Spark VCores
One Capacity Unit (CU) equals two Apache Spark VCores. Fabric capacity is shared across all workspaces assigned to it, and Spark VCores are shared among notebooks, Spark job definitions, and lakehouses within those workspaces.
Operation Types
Fabric classifies operations as interactive (on-demand, like DAX queries) or background (scheduled, like refreshes and Spark jobs). Background operations are smoothed over a 24-hour period. All Spark operations are background operations.
Throttling Behavior
When capacity is fully utilized, new Spark jobs receive HTTP 430 with TooManyRequestsForCapacity. With queueing enabled, pipeline-triggered and scheduled jobs enter a FIFO queue and retry automatically when capacity becomes available.
Capacity SKU Limits
| SKU | Spark VCores | Queue Limit |
|---|---|---|
| F2 | 4 | 4 |
| F4 | 8 | 4 |
| F8 | 16 | 8 |
| F16 | 32 | 16 |
| F32 | 64 | 32 |
| F64 | 128 | 64 |
| F128 | 256 | 128 |
| F256 | 512 | 256 |
| F512 | 1024 | 512 |
What ships with it
8 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.
- LICENSE.txt 11 KB
- references/capacity-health-reference.md 7.5 KB
- references/cost-analysis-reference.md 6.2 KB
- scripts/Get-FabricCapacityHealth.ps1 3.9 KB runs code
- scripts/Get-FabricJobHistory.ps1 5.9 KB runs code
- scripts/Get-FabricSparkConcurrency.ps1 4.9 KB runs code
- scripts/New-FabricPerformanceReport.ps1 9.1 KB runs code
- templates/performance-report.sql 6.2 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.
- 12d ago First seen · 118 lines · 90 tokens per session scan A eee82600d6f4
fabric-performance-monitoring is a skill published in the GitHub repository PatrickGallucci/fabric-skills (16 stars, last pushed 3mo ago), licensed MIT. It adds 90 tokens to every session and 1,282 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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