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 fabioc-aloha/Alex_Skill_Mall --skill microsoft-fabricgit clone --depth 1 https://github.com/fabioc-aloha/Alex_Skill_MallWrote 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/fabioc-aloha/alex_skill_mall/microsoft-fabric)<a href="https://agentmods.dev/skills/fabioc-aloha/alex_skill_mall/microsoft-fabric"><img src="https://agentmods.dev/badge/skills/fabioc-aloha/alex_skill_mall/microsoft-fabric/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/fabioc-aloha/alex_skill_mall/microsoft-fabric"><img src="https://agentmods.dev/badge/skills/fabioc-aloha/alex_skill_mall/microsoft-fabric.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 | $0.00022 | $0.02341 |
| Opus 5 | $0.00011 | $0.01171 |
| Sonnet 5 | $0.00004 | $0.00468 |
| Haiku 4.5 | $0.00002 | $0.00234 |
Grade A, and why
microsoft-fabric 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 8d 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 — 323 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Microsoft Fabric Governance Skill
⚠️ Staleness Watch (Last validated: Feb 2026 — REST API v1): Microsoft Fabric ships major features monthly. Monitor the Fabric release notes for new item types, API surface changes, and Git integration improvements. The REST API base URL (
api.fabric.microsoft.com/v1) is stable but new endpoints are added regularly. See alsoEXTERNAL-API-REGISTRY.md.
Overview
Expert knowledge for Microsoft Fabric workspace management, governance, and documentation. Covers REST API patterns, medallion architecture implementation, permission compliance pipelines, and automated workspace inspection.
Data Project Scaffolding
Recommended Folder Structure
data-project/
├── .github/
│ ├── copilot-instructions.md # Data project context
│ └── prompts/
│ └── pipeline-review.prompt.md
├── docs/
│ ├── DATA-PLAN.md # Project scope, objectives
│ ├── DATA-DICTIONARY.md # Field definitions
│ ├── LINEAGE.md # Data flow documentation
│ └── architecture/
│ └── medallion-design.md
├── pipelines/
│ ├── bronze/ # Raw ingestion
│ │ └── [source]-ingest.py
│ ├── silver/ # Cleansing, standardization
│ │ └── [entity]-transform.py
│ └── gold/ # Business logic, aggregations
│ └── [domain]-model.py
├── notebooks/
│ ├── exploration/ # EDA notebooks
│ └── prototypes/ # Pipeline prototypes
├── schemas/
│ ├── bronze/
│ ├── silver/
│ └── gold/
├── tests/
│ ├── unit/
│ └── data-quality/
├── config/
│ ├── connections.yaml
│ └── environments/
│ ├── dev.yaml
│ └── prod.yaml
└── README.md
DATA-PLAN.md Template
# Data Plan: [Project Name]
## Objective
[What business problem does this data pipeline solve?]
## Data Sources
| Source | Type | Frequency | Volume |
|--------|------|-----------|--------|
| [System A] | [API/Database/File] | [Daily/Hourly/Real-time] | [~X records/day] |
## Medallion Architecture
| Layer | Description | Key Transformations |
|-------|-------------|---------------------|
| Bronze | Raw ingestion from [sources] | Minimal: schema enforcement, timestamps |
| Silver | Cleansed, standardized | Deduplication, type casting, validation |
| Gold | Business-ready | Joins, aggregations, business logic |
## Data Quality Rules
| Rule | Layer | Implementation |
|------|-------|----------------|
| No nulls in [field] | Silver | Validation check |
| Referential integrity | Gold | Foreign key check |
## Success Criteria
- [ ] All sources ingesting to Bronze
- [ ] Silver quality checks passing
- [ ] Gold tables serving [consumers]
- [ ] Documentation complete
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.
- 8d ago First seen · 323 lines · 22 tokens per session scan A 846d90f14c65
microsoft-fabric is a skill published in the GitHub repository fabioc-aloha/Alex_Skill_Mall (4 stars, last pushed today), licensed MIT. It adds 22 tokens to every session and 2,341 once invoked, about $0.0001 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 2026-09-03.
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