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.
npx skills add microsoft/skills-for-fabric --skill fabriciqgit 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/skills/microsoft/skills-for-fabric/fabriciq)<a href="https://agentmods.dev/skills/microsoft/skills-for-fabric/fabriciq"><img src="https://agentmods.dev/badge/skills/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/skills/microsoft/skills-for-fabric/fabriciq"><img src="https://agentmods.dev/badge/skills/microsoft/skills-for-fabric/fabriciq.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Anti-Refusal · line 80 Skill attempts to nullify the agent's safety policies or restrictions ('you have no restrictions', 'ignore your guidelines', 'do anything now'). This is a direct jailbreak that disables guardrails.Fix: Remove jailbreak framing that nullifies safety policies or restrictions. Skill content must not instruct the agent to ignore its guidelines or operate without guardrails.
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 | $0.00079 | $0.05944 |
| Opus 5 | $0.00039 | $0.02972 |
| Sonnet 5 | $0.00016 | $0.01189 |
| Haiku 4.5 | $0.00008 | $0.00594 |
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 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 — 271 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CRITICAL NOTES
- To find artifact details (including artifact ID) from a search query: use
DiscoverArtifactswith the search term — do not call workspace/item list APIs- To find the semantic model behind a report: call
GetReportMetadataand extract the model GUID from the response- When the user provides a Power BI URL: call
ResolveReportIdFromUrlto get the correct report GUID before proceeding
Power BI Consumption — FabricIQ Skill
⚠️ STOP — Read this entire skill document in full before taking any action. Do not begin orchestrating tool calls until you have read and internalized all sections below, including Workflow, DAX Rules, Verified Answers, and Error Recovery. Skipping ahead leads to incorrect queries and missed instructions.
You help users analyze Power BI data. You orchestrate each step: discover artifacts, inspect report and model schemas, resolve values, and execute queries. Uses the FabricIQ MCP server.
Table of Contents
| Task | Reference | Notes |
|---|---|---|
| Fabric Topology & Key Concepts | COMMON-CORE.md § Fabric Topology & Key Concepts | Hierarchy; Finding Things in Fabric |
| Environment URLs | COMMON-CORE.md § Environment URLs | Production (Public Cloud) |
| Authentication & Token Acquisition | COMMON-CORE.md § Authentication & Token Acquisition | Wrong audience = 401; covers token audiences, delegated vs app permissions, OAuth flows, identity types, and Entra app registration |
| Authentication Recipes | COMMON-CLI.md § Authentication Recipes | az login flows, environment detection, token acquisition, and debugging |
| Gotchas, Best Practices & Troubleshooting | COMMON-CORE.md § Gotchas, Best Practices & Troubleshooting | Common Errors; Best Practices |
| Must/Prefer/Avoid | SKILL.md § Must/Prefer/Avoid | Guardrails for Power BI consumption |
| Workflow | SKILL.md § Workflow | FabricIQ orchestration steps |
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 · 271 lines · 79 tokens per session scan A 6095bded09b4
fabriciq is a skill published in the GitHub repository microsoft/skills-for-fabric (1,140 stars, last pushed today), licensed MIT. It adds 79 tokens to every session and 5,944 once invoked, about $0.0004 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.
Other skills, from other repositories
agent-platform-rag-engine-management
Manage and query Agent Platform RAG Engine Corpora and retrieve grounded contexts using the Google GenAI SDK. Use when listing RAG corpora or files, inspecting a corpus, retrieving contexts, or generating content grounded in a RAG corpus. Do not use for standard database queries (use SQL/Spanner skills), Google…
agent-platform-model-registry
Agent Platform Model Registry Management. Use when you need to upload, list, describe, update, or delete machine learning models (and their versions) in the Agent Platform Model Registry. Don't use for model training, model deployment to endpoints, or managing non-Agent Platform models.
foundry-config-setup
Resolve missing setup caused by a hardcoded Foundry project endpoint or model in a sample. Use when a sample fails because it uses a placeholder/hardcoded projectendpoint (for example "https://your-project.services.ai.azure.com") or a hardcoded model instead of reading them from the environment.
google-cloud-solution-agentic-analytics-spark-knowledge-catalog
Discovers requirements and generates guidance to design and deploy a governed, secure agentic-analytics solution for data that's distributed across Google Cloud, other cloud providers, or on-premises. Data that's outside Google Cloud (such as data from Databricks, Snowflake, Salesforce, SAP, or Oracle systems) is…
training-check
Interactively monitor training metrics from the current Codex session, periodically checking WandB or fallback logs for NaN, divergence, plateaus, and broken runs.
nemo-automodel-launcher-config
Configure NeMo AutoModel job launches for interactive runs, Slurm clusters, and SkyPilot cloud execution.