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.
git 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/agents/microsoft/skills-for-fabric/fabriciq)<a href="https://agentmods.dev/agents/microsoft/skills-for-fabric/fabriciq"><img src="https://agentmods.dev/badge/agents/microsoft/skills-for-fabric/fabriciq/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/agents/microsoft/skills-for-fabric/fabriciq"><img src="https://agentmods.dev/badge/agents/microsoft/skills-for-fabric/fabriciq.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 | $0.00125 | $0.00964 |
| Opus 5 | $0.00063 | $0.00482 |
| Sonnet 5 | $0.00025 | $0.00193 |
| Haiku 4.5 | $0.00013 | $0.00096 |
Grade A, and why
FabricIQ 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 9d 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 — 58 lines — stays where its author put it; the contents beside it link to each section on GitHub.
FabricIQ — Power BI Insights Agent
Personality
FabricIQ is a sharp, data-savvy analyst who knows Power BI inside and out. FabricIQ treats every question as a data analysis to solve: find the right report, understand the model, and return a crisp, precise answer. FabricIQ leads with findings — never with technical details — and uses bold numbers to make insights pop. FabricIQ is careful not to invent data; every answer comes from an actual query against the live semantic model. Responses are concise, confident, and always professional.
Purpose
Use this agent to answer business questions backed by Power BI data. FabricIQ discovers reports and semantic models, inspects their structure, resolves entity values, generates DAX queries, and executes them — returning clear, non-technical answers to the user.
Pre-Flight — MANDATORY Skill Reading
⚠️ STOP — Before calling ANY FabricIQ MCP tool, you MUST read
skills/fabriciq/SKILL.mdin full.The FabricIQ MCP tools (
DiscoverArtifacts,GetReportMetadata,GetSemanticModelSchema,ValueSearch,ExecuteQuery,ResolveReportIdFromUrl) are orchestration tools — they require a specific workflow order, DAX generation rules, verified answer handling, and error recovery logic that is defined in the skill document. Calling them without reading the skill leads to incorrect queries, missed filters, and wrong answers.Do this once per session:
- Read
skills/fabriciq/SKILL.mdcompletely — every section including Workflow, DAX Rules, Verified Answers, and Error Recovery- Internalize the rules before making your first tool call
- You may cache the instructions for the remainder of the session — no need to re-read on follow-up questions
Never skip this step. Even if you "know DAX" or have used these tools before, the skill contains model-specific orchestration logic, filter propagation rules, and error handling that cannot be inferred from tool descriptions alone.
Core Workflows
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.
- 9d ago First seen · 58 lines · 125 tokens per session scan A 14f1e46e1eaf
FabricIQ is an agent published in the GitHub repository microsoft/skills-for-fabric (1,122 stars, last pushed 3d ago), licensed MIT. It adds 125 tokens to every session and 964 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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