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-spark-perf-remediategit 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-spark-perf-remediate)<a href="https://agentmods.dev/skills/patrickgallucci/fabric-skills/fabric-spark-perf-remediate"><img src="https://agentmods.dev/badge/skills/patrickgallucci/fabric-skills/fabric-spark-perf-remediate/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-spark-perf-remediate"><img src="https://agentmods.dev/badge/skills/patrickgallucci/fabric-skills/fabric-spark-perf-remediate.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 | $0.00140 | $0.01851 |
| Opus 5 | $0.00070 | $0.00925 |
| Sonnet 5 | $0.00028 | $0.00370 |
| Haiku 4.5 | $0.00014 | $0.00185 |
Grade A, and why
fabric-spark-perf-remediate 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 — 160 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Microsoft Fabric Apache Spark Performance remediate
Systematic workflows for diagnosing, analyzing, and resolving Apache Spark performance problems in Microsoft Fabric Data Engineering and Data Science workloads.
When to Use This Skill
Activate when encountering any of the following scenarios:
- Spark notebooks or jobs running slower than expected
- Capacity throttling errors (HTTP 430 / TooManyRequestsForCapacity)
- Data skew detected by Spark Advisor in notebook cells
- Excessive shuffle read/write in Spark UI stages
- Small files accumulation in Delta Lake tables
- Streaming ingestion throughput degradation
- Need to select or tune a Fabric Spark resource profile
- VOrder vs. Optimized Write decision-making
- Autotune configuration and validation
- Right-sizing Spark pools, node counts, or Fabric capacity SKUs
Prerequisites
- Access to a Microsoft Fabric workspace with Data Engineering enabled
- Contributor or higher role on the workspace
- Familiarity with PySpark or Spark SQL
- PowerShell 7+ (for diagnostic scripts)
- Fabric REST API access token (for API-based diagnostics)
Quick Diagnosis Decision Tree
Start here when a Spark job is slow:
-
Is the job queued or throttled? Check Monitoring Hub for HTTP 430.
- Yes → See Capacity and Concurrency Tuning
- No → Continue
-
Did the Spark Advisor flag warnings? Check notebook cell indicators.
- Data Skew detected → See Data Skew Resolution
- No warnings → Continue
-
Is a single stage disproportionately slow? Open Spark UI → Stages tab.
- Yes, shuffle stage → See Shuffle Optimization
- Yes, scan stage → See File Scan Optimization
- No → Continue
-
Are executors underutilized? Check Resources tab in monitoring detail.
- High idle cores → See Pool and Executor Sizing
- All cores busy → See Partitioning Strategy
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.
- 12d ago First seen · 160 lines · 140 tokens per session scan A c60b5e20e501
fabric-spark-perf-remediate is a skill published in the GitHub repository PatrickGallucci/fabric-skills (16 stars, last pushed 3mo ago), licensed MIT. It adds 140 tokens to every session and 1,851 once invoked, about $0.0007 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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