fabric-data-agentlisted

Use when configuring Microsoft Fabric Data Agents (GA March 2026) — conversational Q&A over Lakehouse / Warehouse / KQL / Semantic Model / Fabric SQL DB / Mirrored DB / Ontology / MS Graph (≤5 sources per agent), consumed in-product or via the agent's MCP endpoint (Assistants API and Copilot-in-Power-BI paths retired 2026-08-26). Covers the four configuration layers (agent instructions, data source instructions, descriptions for routing, example queries ≤100/source), when to use vs semantic-model AI instructions, governance precedence (organizational → role-based → developer → user), best practices (right-layer scoping, iteration, version control), and key limitations (read-only, structured data only, English only, 25-row/25-col response cap, no example queries on semantic models). The Creator Agent ('Build agent with AI', SQL/Eventhouse only), MCP endpoint, M365 Copilot Agent Store, Python SDK, Copilot Studio, Azure AI Foundry, and service-principal auth (not Foundry/Copilot or KQL) remain in preview.
wardawgmalvicious/agent-config · ★ 1 · AI & Automation · score 77

Install: claude install-skill wardawgmalvicious/agent-config

# Configuring Fabric Data Agents A practical, reusable guide for configuring a Fabric Data Agent so it returns accurate, contextually relevant answers. Use this template across projects — replace the example domain (retail / sales / logistics) with your own without changing the structure. ## What a Data Agent is A Fabric Data Agent is a conversational Q&A interface. It accepts natural-language questions, routes them to the right data source, generates a query (SQL / DAX / KQL / Microsoft Graph), validates it, executes it read-only, and returns a human-readable answer. Supported data sources: **Lakehouse, Warehouse, KQL Database (Eventhouse), Power BI Semantic Model, Fabric SQL Database, Mirrored Database, Ontology, Microsoft Graph**. A single agent supports up to **5 data sources in any combination**. Read-only by design — it never generates create/update/delete queries. **Ontology as a source** is the one entry there that is a whole item type of its own — see `fabric-ontology` for modelling it, binding it to data, and its semantic enrichment, which is what makes an ontology-grounded agent answer well. Three data-agent-side behaviours belong here rather than there: an ontology source is still **preview**, the agent's first few queries after creation can fail while it initializes (wait and retry), and **aggregation is a known gap** — add the instruction `Support group by in GQL` to the agent's instructions. **GA since March 2026** for the core surface: create / configure