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-dataflows-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-dataflows-perf-remediate)<a href="https://agentmods.dev/skills/patrickgallucci/fabric-skills/fabric-dataflows-perf-remediate"><img src="https://agentmods.dev/badge/skills/patrickgallucci/fabric-skills/fabric-dataflows-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-dataflows-perf-remediate"><img src="https://agentmods.dev/badge/skills/patrickgallucci/fabric-skills/fabric-dataflows-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 | $0.00118 | $0.02573 |
| Opus 5 | $0.00059 | $0.01287 |
| Sonnet 5 | $0.00024 | $0.00515 |
| Haiku 4.5 | $0.00012 | $0.00257 |
Grade A, and why
fabric-dataflows-perf-remediation 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 11d 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 — 253 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Dataflows Gen2 Performance Troubleshooting
Systematic diagnostic workflows for identifying and resolving performance issues in Microsoft Fabric Dataflow Gen2 workloads covering data movement, transformation execution, staging configuration, and destination write optimization.
When to Use This Skill
- Dataflow Gen2 refresh takes longer than expected
- Fast Copy is not being utilized or is failing
- Query folding indicators show red or yellow steps
- Staging-to-destination data movement is a bottleneck
- Gateway-connected dataflows have high latency
- Incremental refresh is slower than full refresh
- Capacity throttling affects dataflow execution
- Refresh failures with permission or connector errors
- Need to automate dataflow monitoring and health checks
- Migrating from Dataflow Gen1 and seeing performance regressions
Prerequisites
- Microsoft Fabric workspace with Data Factory enabled
- Contributor or higher role on the workspace
- PowerShell 7+ with Az.Accounts module for automation scripts
- Access to Fabric Monitoring Hub for refresh history analysis
- Fabric Capacity Metrics app access for CU consumption review
Quick Diagnosis: Symptom-to-Solution Map
| Symptom | Likely Cause | Jump To |
|---|---|---|
| Refresh takes 2x+ longer than Gen1 | Delta Parquet output overhead or staging misconfiguration | Consideration 5 in Performance Guide |
| Fast Copy not activating | Unsupported connector or non-foldable transforms | Fast Copy Diagnostics |
| "Insufficient permissions for staging artifacts" | Creator token expired (90+ days) | Common Errors |
| Slow design-time previews | Large dataset loaded in editor | Design-Time Optimization |
| Staging-to-Lakehouse write is slow | Extra data hop through staging Warehouse | Staging Strategy |
| Gateway dataflows are slow | All transforms running on gateway host | Gateway Optimization |
| Incremental refresh slower than full | Too many small buckets creating overhead | Incremental Refresh Tuning |
| HTTP 430 / capacity throttled | Concurrent Spark jobs exhausting CUs | Capacity Management |
What ships with it
5 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.
- 11d ago First seen · 253 lines · 118 tokens per session scan A 0ca02e143e24
fabric-dataflows-perf-remediation is a skill published in the GitHub repository PatrickGallucci/fabric-skills (16 stars, last pushed 3mo ago), licensed MIT. It adds 118 tokens to every session and 2,573 once invoked, about $0.0006 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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