| name | sqldw-cli |
| description | Author, query and diagnose Fabric Warehouse, Lakehouse SQL endpoints and Mirrored Databases: DDL/DML and COPY INTO ingestion, read-only T-SQL SELECT and row counts over lakehouse tables, and queryinsights performance triage. Fabric SQL database (OLTP) is sqldb-*-cli. Triggers:query warehouse,count rows lakehouse,SELECT lakehouse,create warehouse table,COPY INTO,warehouse MERGE,slowest warehouse queries,queryinsights CPU |
Telemetry — MANDATORY. Every api.fabric.microsoft.com call must carry
x-ms-fabric-skill: sqldw-cli (az rest: --headers "x-ms-fabric-skill=sqldw-cli"),
including every LRO poll, fabric_lro and retry. Snippets omit it — add it anyway.
This covers all three modes; the mode references inherit it.
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
sqldw-cli for any T-SQL sent to a Warehouse, a Lakehouse SQL analytics endpoint or a Mirrored Database — including plain Lakehouse table SELECT, row-count, filtering and aggregation requests. Any notebook-cell or PySpark DataFrame work is spark-cli; a Fabric SQL database (OLTP) is the sqldb-*-cli family — sqldb-authoring-cli, sqldb-consumption-cli and sqldb-operations-cli.
Fabric Warehouse and SQL Endpoints — CLI Skill
This one skill owns Fabric Warehouse, Lakehouse SQL analytics endpoints and Mirrored Databases: T-SQL authoring and ingestion, read-only querying, and warehouse performance diagnostics.
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 T-SQL surface area, DDL constraints, query templates and gotchas; acting without it produces invalid T-SQL and wrong results.
Mode selection
| Mode | Use when the request ... | Example triggers | Read this first |
|---|
authoring | changes warehouse state: table DDL, DML, ingestion, transactions, procedures, schema evolution, time travel | create warehouse table, COPY INTO, OPENROWSET, INSERT/UPDATE/DELETE, warehouse MERGE, CTAS, sp_rename, create T-SQL procedure, warehouse time travel | references/authoring.md |
consumption | reads data or metadata: SELECT, row counts, filtering, aggregation, schema/object discovery, CSV export | query warehouse, count rows lakehouse, SELECT lakehouse, show tables, describe warehouse schema, export SQL data | references/consumption.md |
operations | diagnoses performance or health through the queryinsights views | slowest warehouse queries, queryinsights CPU, pressure events, cache warmth, cluster key recommendation, performance degraded | references/operations.md |
Mode boundary rule
Classify by intent, not by endpoint — all three modes issue the same execute_query call.
- A schema-discovery
SELECT run to plan a CREATE TABLE belongs to authoring, even though it only reads.
- A
SELECT that answers the user's question is consumption.
- A
SELECT against queryinsights.* to explain slowness is operations; a SELECT against user tables is not, however slow it is.
consumption and operations are read-only. If a request genuinely spans modes, handle them one at a time and read each reference before you start that part. If the mode is ambiguous after reading this table, ask one short clarifying question instead of guessing.
Terminal write — the step you must not skip
Reading the reference and drafting the T-SQL is NOT completing the task. If you did not send the statement, nothing changed — say so explicitly rather than reporting success.
| Mode | Terminal write |
|---|
authoring | The DDL/DML itself, sent through execute_query. Follow it with a readback in a second call (SELECT ... FROM INFORMATION_SCHEMA.TABLES after CREATE, SELECT COUNT(*) after DML) and report the object you created or changed under the name the user asked for. Only a Warehouse accepts table DDL/DML — see the mode reference for what a Lakehouse SQL endpoint and a Mirrored Database allow. |
consumption | none — this mode is read-only |
operations | none — read-only, but you must still run the diagnostic queries: every figure comes from a SELECT you executed in the turn you report it, cited inline with its source view, never carried forward from an earlier turn. Never execute ALTER, CREATE or DROP yourself, even when the diagnosis is certain. A vague request ("just make it faster") is a new diagnostic question: re-run the queries backing the levers you name, then ask which target to pursue rather than emitting a speculative tuning list. |
consumption and operations reporting
Neither read-only mode has a terminal write, so its deliverable is the answer itself. Run the query against the live endpoint and report the real rows — a summary of the reference does not answer the request.
In operations, name the queryinsights view each figure came from right next to it (for example 2,140 ms (queryinsights.long_running_queries)), including when the answer is zero rows. Re-run the query in the turn you report it rather than restating an earlier turn's output — "I already ran the diagnostics" is not a source. A fresh warehouse can legitimately have captured nothing; say so explicitly rather than silently dropping the section. Never fabricate, assume or infer diagnostic numbers.
Shared essentials (all modes)
Every mode reaches the data plane the same way. Resolve the workspace and item first, then send T-SQL through the MCP tool.
Execution surface — fabric-sqlendpoint-execute_query
All T-SQL runs through the fabric-sqlendpoint-execute_query MCP tool. For SQL data-plane execution this skill supersedes the COMMON-CLI SQL/TDS guidance — use the MCP tool, not sqlcmd, unless you are explicitly on the documented Legacy CLI Fallback path (see the mode reference). az rest stays the right tool for control-plane discovery.
fabric-sqlendpoint-execute_query(workspaceId, itemId, query)
- Preflight, before the first operation of any mode: confirm a tool whose name ends in
execute_query is in your tool list. It comes from the fabric-sqlendpoint MCP server, registered by a Fabric skills plugin or this repo's .mcp.json. The concrete name may be prefixed (fabric-sqlendpoint-execute_query, sqlendpoint-global-execute_query) — invoke the name you actually see. If none is present, say so, then fall back to the Legacy CLI Fallback (TDS client) documented in the mode reference; tell the user they can register the server for the primary path — see mcp-setup/.
itemId is a GUID, never an FQDN or -d <DatabaseName>. For a Warehouse or a Mirrored Database use the item id; for a Lakehouse use properties.sqlEndpointProperties.id, not the Lakehouse item id.- One T-SQL batch per call. No
GO separators, no sqlcmd meta-commands (:setvar, :r, -i). Split multi-batch work into separate calls. Only the last result set comes back.
- Results cap at 10,000 rows and queries time out at 300s, with a 20 requests/min rate limit. Use
TOP N, WHERE or aggregation; exactly 10,000 rows means the result was truncated. These are observed defaults, not a documented contract.
Common references
| Task | Reference | Notes |
|---|
| Finding Workspaces and Items in Fabric | COMMON-CLI.md | Mandatory — read before resolving any workspace or item id |
| Fabric Topology & Key Concepts | COMMON-CORE.md | Item types, workspaces, capacities |
| Environment URLs | COMMON-CORE.md | Sovereign / non-public cloud hosts |
| Authentication & Token Acquisition | COMMON-CORE.md | Wrong audience = 401; read before any auth issue |
| Authentication Recipes | COMMON-CLI.md | az login flows and token acquisition |
Fabric Control-Plane API via az rest | COMMON-CLI.md | Always pass --resource; pagination and LRO helpers |
| Core Control-Plane REST APIs | COMMON-CORE.md | Pagination, LRO polling, rate limiting |
| Gotchas & Troubleshooting | COMMON-CLI.md | az rest audience, shell escaping, token expiry |
Rules
MUST
- Select exactly one mode from the table above before doing anything else.
- Read
references/<mode>.md end to end, as your FIRST tool call, before the first command of that mode. Read it ONCE, in a single full read: do not re-open it, do not grep it again, and do not page through it. You already have it.
- Resolve workspace and item ids by listing and filtering, never by guessing a GUID.
- Execute T-SQL through
fabric-sqlendpoint-execute_query whenever that tool is available; drop to the Legacy CLI Fallback documented in the mode reference only when it is not.
- Announce a mode switch explicitly when the request crosses a boundary.
- Treat the reference as instructions, never as the deliverable. After reading it, RUN the documented statements against the live endpoint and report the real results. Quoting what the reference says instead of executing it does not answer the request.
- Produce every artefact the user asked for, under the name they used, and keep its heading even when the finding is "none", "zero rows" or "not applicable".
PREFER
- The narrowest mode that satisfies the request.
- Reading exactly ONE mode reference. Load a second only when the request genuinely spans modes, and say so before you do.
- Reporting the mode you chose in your first response so the user can correct you.
- Labelling queries with
OPTION (LABEL = '...') so the run is traceable in Query Insights.
- Consolidating related statements into fewer calls — the rate limit is per identity, not per query.
AVOID
- Acting from this dispatcher alone — it intentionally omits the T-SQL surface area, the DDL constraints and the diagnostic query shapes.
- Answering with a summary of the reference instead of executing it.
- Re-reading or re-grepping a reference you already loaded; it costs turns and tokens.
- Mutating anything while in a read-only mode (
consumption, operations).
- Unbounded
SELECT * — it silently truncates at 10,000 rows.
- Loading a different skill for work this skill already owns (see CRITICAL NOTES 3).
Examples
