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 fabriciq-ontology-cligit 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-ontology-cli)<a href="https://agentmods.dev/skills/microsoft/skills-for-fabric/fabriciq-ontology-cli"><img src="https://agentmods.dev/badge/skills/microsoft/skills-for-fabric/fabriciq-ontology-cli/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-ontology-cli"><img src="https://agentmods.dev/badge/skills/microsoft/skills-for-fabric/fabriciq-ontology-cli.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00060 | $0.01590 |
| Opus 5 | $0.00030 | $0.00795 |
| Sonnet 5 | $0.00012 | $0.00318 |
| Haiku 4.5 | $0.00006 | $0.00159 |
Grade A, and why
fabriciq-ontology-cli 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 — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Telemetry — MANDATORY. Every
api.fabric.microsoft.comcall must carryx-ms-fabric-skill: fabriciq-ontology-cli(az rest:--headers "x-ms-fabric-skill=fabriciq-ontology-cli"), including every LRO poll,fabric_lroand retry. Snippets omit it — add it anyway.
CRITICAL NOTES
- To find the workspace details (including its ID) from workspace name: list all workspaces and, then, use JMESPath filtering
- To find the item details (including its ID) from workspace ID, item type, and item name: list all items of that type in that workspace and, then, use JMESPath filtering
- Skill disambiguation: use
fabriciq-ontology-clifor the Ontology item itself. Natural-language questions over Power BI reports and dashboards arefabriciq; DAX against a semantic model issemantic-model-cli.
Fabric IQ Ontology -- CLI Skill
This one skill owns Fabric IQ Ontology items: entity and relationship types, bindings, definitions, lineage, grounding and graph walks.
It is a mode dispatcher and contains NO procedures. Pick the mode that matches the request from the table below, then read the matching references/<mode>.md file end to end with your file-reading tool BEFORE issuing a single command. That file holds the endpoints, payload shapes, templates and gotchas; acting without it produces wrong payloads and wrong results.
Mode selection
| Mode | Use when the request ... | Example triggers | Read this first |
|---|---|---|---|
authoring |
creates or updates an Ontology item, entity/relationship types, or data bindings, and previews/confirms a definition change | create ontology item, bind entity type, add relationship type, update ontology definition | references/authoring.md |
consumption |
explores an existing ontology: schema, entity types, bindings, lineage, grounding extraction, graph walks, summaries | entity types, ground query, ontology lineage, walk the graph, summarize the ontology | references/consumption.md |
What ships with it
12 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.
- references/authoring.md 47 KB
- references/authoring/authoring-mechanics.md 18 KB
- references/authoring/definition-script-templates.md 12 KB
- references/authoring/examples.md 9.8 KB
- references/authoring/ONTOLOGY-AUTHORING-CORE.md 17 KB
- references/authoring/preview-and-confirm.md 13 KB
- references/consumption.md 35 KB
- references/consumption/examples.md 7.8 KB
- references/consumption/graph-walks.md 14 KB
- references/consumption/grounding-extraction.md 14 KB
- references/consumption/query-pattern.md 2.8 KB
- references/consumption/routing.md 13 KB
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 · 91 lines · 60 tokens per session scan A 95b93109e869
fabriciq-ontology-cli is a skill published in the GitHub repository microsoft/skills-for-fabric (1,140 stars, last pushed yesterday), licensed MIT. It adds 60 tokens to every session and 1,590 once invoked, about $0.0003 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
pinecone
Managed vector DB for production RAG and search.
embeddings
Vector embeddings with HNSW indexing, sql.js persistence, and hyperbolic support. 75x faster with agentic-flow integration. Use when: semantic search, pattern matching, similarity queries, knowledge retrieval. Skip when: exact text matching, simple lookups, no semantic understanding needed.
data-engineer
Build scalable data pipelines, modern data warehouses, and real-time streaming architectures. Implements Apache Spark, dbt, Airflow, and cloud-native data platforms.
graphjin-env
Use when setting up a training or evaluation loop against a GraphJin agent environment — running the container, reading /health, driving episodes hosted or step-by-step or with your own agent over MCP, splitting train from eval, exporting trajectories, and deciding whether two rewards can be compared.
ingesting-into-data-lake
Import data into the AWS data lake from S3 files, local uploads, JDBC databases (Oracle, SQL Server, PostgreSQL, MySQL, RDS, Aurora), Amazon Redshift, Snowflake, BigQuery, DynamoDB, or existing Glue catalog tables (migration). Default target is S3 Tables; standard Iceberg on a general purpose bucket is supported where…
similarity-search-patterns
Implement efficient similarity search with vector databases. Use when building semantic search, implementing nearest neighbor queries, or optimizing retrieval performance.