Onelake Catalog CLI
MicrosoftOfficialPublished by Microsoft
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- Workflow
- Automation and integrations
- MIT
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AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
The onelake-catalog-cli skill provides a structured interface for managing the Microsoft Fabric OneLake catalog. It operates through distinct modes for governance auditing and metadata curation, ensuring that actions are performed with appropriate permissions and safety gates. The skill supports tenant-wide admin audits, data-owner governance checks, and item-level metadata curation, including descriptions, tags, and table/column metadata. It enforces strict write-gating and requires explicit owner approval for all changes to ensure data integrity and security.
What it does
- Audits tenant-wide or workspace-specific governance posture.
- Curates item metadata including descriptions, display names, and tags.
- Manages table and column descriptions for items with OneLake Tables.
- Performs guarded remediation for domains, workspace assignments, and capacities.
- Provides dry-run capabilities for governance and remediation tasks.
- Enforces strict write-gates requiring explicit user approval for all changes.
When to use it
- When you need to audit governance posture across a Fabric tenant or specific workspaces.
- When an item owner needs to improve discoverability through metadata curation.
- When a data owner needs to remediate workspace domain, capacity, or tag assignments.
- When a tenant admin needs to perform bulk governance updates or policy enforcement.
Advantages
- Provides a unified, mode-based workflow for both auditing and remediation.
- Enforces safety by requiring explicit approval for all write operations.
- Supports granular, least-privileged access for data owners.
- Includes built-in logic for handling long-running operations and API rate limits.
- Ensures governance findings are actionable and prioritized.
Usage examples
- “Propose a better description for the semantic model Sales Model in the Finance workspace.”
- The agent will read the current item metadata, draft a suggested description based on content, and present it for owner approval before applying the change.
- “Audit our tenant's OneLake catalog governance posture and prioritize the findings.”
- The agent will perform a tenant-wide audit, applying the necessary scope filters, and report findings categorized by pillar with recommended actions.
- “Which workspaces I administer are not assigned to a domain?”
- The agent will identify and list all workspaces within the caller's scope that lack a domain assignment.
- “Show a dry run for assigning these workspaces to the Finance domain, including current assignments.”
- The agent will perform a read-only check to display the current domain assignments and the proposed changes for the specified workspaces.
Install
Download the skill as a ZIP:
https://autogineer.com/agent-skills/microsoft/onelake-catalog-cli/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip onelake-catalog-cli.zip -d .agents/skills
Documentation by Microsoft
Telemetry — MANDATORY. Every
api.fabric.microsoft.comcall must carryx-ms-fabric-skill: onelake-catalog-cli(az rest:--headers "x-ms-fabric-skill=onelake-catalog-cli"), including every LRO poll,fabric_lroand retry. Snippets omit it — add it anyway.
CRITICAL NOTES
To find the workspace ID from its name, one call:
az rest --method get --resource "https://api.fabric.microsoft.com" --url "https://api.fabric.microsoft.com/v1/workspaces" --query "value[?displayName=='<name>'] | [0].id" -o tsv(followcontinuationTokenonly if it isn't on the first page; details in COMMON-CLI.md § Finding Workspaces and Items in Fabric).To find an item's ID, one call: the same on
.../v1/workspaces/{ws}/items?type=<Type>with--query "value[?displayName=='<name>'] | [0].id".Write-gated skill — never call a write API before its gate below has passed. For curation that means the owner reviewed every proposed change and explicitly confirmed — not even a "test" write to check whether a change is allowed or what is already applied.
The item list and Get Item both return an item's
tags. An item with no tags has notagsfield — that absence means untagged.
OneLake Catalog — CLI Skill (mode dispatcher)
One skill for the OneLake catalog. Govern (catalog health, protection and trust: audits and guarded remediation, by permission tier) and curate (an owner improving specific items' discoverability metadata) are modes, each detailed in a reference loaded on demand. This file picks the mode, holds every write gate, and indexes the references.
Mode selection
| Mode | Use when | Load | Writes |
|---|---|---|---|
| curate | An owner wants specific items easier to find: a description, a clearer display name, tags, or table and column descriptions (items with a OneLake Tables folder) — one item, an explicit list, or one named workspace's weakly-described items | references/curate.md | ✅ after the owner approves each suggestion |
| dataowner-audit | A non-admin workspace or domain owner wants governance posture for workspaces they administer (widen to accessible on request; Core API) | references/dataowner-audit.md | ❌ |
| dataowner-remediate | A data owner who is also a domain / workspace / capacity admin fixes a governance finding — single-workspace domain or capacity assignment, workspace tags, refresh, item identity (Core & Power BI APIs, no tenant admin), including dry runs of these | references/dataowner-remediate.md | ✅ self-service |
| admin-audit | A Fabric tenant admin wants tenant-wide governance posture (/v1/admin/*) | references/admin-audit.md; any tenant count starts from admin-audit-scope.md | ❌ |
| admin-remediate | A Fabric tenant admin makes tenant-wide writes — domains, bulk assignment, domain roles, bulk labels, tenant tag definitions, tenant settings | references/admin-remediate.md | ✅ |
Govern is a 2×2 grid — tier (which API surface the caller can reach) × action (audit vs
remediate) — covering the health, protect and trust pillars. Choose the tier by API surface,
not job title: the admin-* modes need the Fabric tenant administrator role (Fabric admin /
Power Platform admin / M365 global admin); domain, capacity and workspace admins who are not
tenant admins live entirely in the dataowner-* modes.
Mode boundary rules
A direct curation request goes straight to curate. Read the target item's current state — don't run a governance audit first. Curation needs neither tenant admin nor workspace Admin; each change has its own permission (see curate.md).
Governance starts with an audit. Never remediate before establishing the current state; audit → remediate within the same tier unless the caller's rights change.
Curate is the only writer of item metadata. Item descriptions and display names, applying or removing an item's tags, and table and column descriptions are written only in curate. Workspace tags stay in dataowner-remediate; tenant tag definitions in admin-remediate.
Govern finds, curate fixes. Govern reports description and tag coverage — presence, with scope, denominator and freshness caveats, not proof the text is accurate; curate judges content and proposes. To fix selected gaps, hand off to curate with: a bounded target (an explicit item list with workspace ID, item ID and type, or one named workspace — never the whole tenant: ask the user to pick), the observed gap with its source and time (a candidate to recheck, not current truth), only the fields the user chose ("fix missing descriptions" = description only), and known access limits and owner contacts. A remediation is done only when curate has verified the write.
Audit modes never write. If a write is asked for in an audit mode, switch explicitly to the matching remediate mode or to curate — don't improvise a write.
A dry run or preflight of a fix loads that fix's remediate mode and stays read-only there — it isn't an audit. Moving one workspace to a domain is
dataowner-remediate; bulk assignment isadmin-remediate.Finding items when the workspace isn't known belongs to
search-consumption-cli. Looking up a workspace or domain by name, or an item by name inside a known workspace, is not discovery: use the lookups in CRITICAL NOTES and don't loadsearch-consumption-clifor it.
⚠️ Known Fabric gap. A domain or workspace admin who is not a tenant admin has no API for their scoped governance posture:
/v1/admin/*rejects them and the Core API can't list a domain's workspaces.dataowner-auditcovers only workspaces the caller can access — say so up front rather than routing into anadmin-*mode that will 401/403.
Terminal write — the step you must not skip
Reading a reference, drafting suggestions or building a dry run is NOT completing a write. Each writing mode ends with the state-changing call(s) below, issued only after the gate for that write passes. If you did not issue it, nothing changed — say so rather than reporting success.
| Mode | Terminal write |
|---|---|
curate | PATCH /v1/workspaces/{ws}/items/{id} (description; display name in a separate call), POST .../items/{id}/applyTags or unapplyTags, and for a table POST https://onelake.table.fabric.microsoft.com/common/v1/{ws}/{item}/schemas/{schema}/tables/{table}/additionalMetadata with the complete set from a fresh read — only for suggestions the owner accepted |
dataowner-remediate | POST /v1/workspaces/{id}/assignToDomain / unassignFromDomain (synchronous 200), assignToCapacity (202 — poll to a terminal state), POST /v1/workspaces/{id}/applyTags / unapplyTags (workspace tags), item identity, semantic model refresh |
admin-remediate | /v1/admin/* writes — domains, bulk workspace assignment, domain roles, labels, tenant tag definitions, tenant settings |
dataowner-audit, admin-audit | none — read-only |
Before reporting a write done, confirm an explicit success (200/201, or a terminal LRO
success for a 202) and read the result back.
Write gates — must pass first
| Write | Mode | Gate |
|---|---|---|
| Any curation write | curate | The owner saw a numbered current → proposed preview of every suggestion and explicitly approved; "apply all" covers only what was shown. Approving an audit or picking a remediation never approves text the owner hasn't seen. |
| Table and column descriptions | curate | A write replaces the table's whole additional metadata: re-read, change only the approved descriptions, send the complete set in the same command, read again. The API has no concurrency check — never claim concurrent edits were preserved. A shortcut table is written on its source — name it and get explicit confirmation. |
| Delete a domain | admin | Check subdomains (parentDomainId) and assigned-workspace counts for the domain and every subdomain; if workspaces would be orphaned, STOP and get explicit confirmation naming them. The API has no cascade-block. See domain-crud.md. |
| Delete a tag definition | admin | Report how many items carry it first — deletion detaches it everywhere with no undo. |
| Bulk-assign workspaces to a domain | admin | Check each target's current domainId and warn before silently overriding an assignment. Dry-run the target list first. |
| Remove a principal from a domain role | admin | Confirm it will not leave the domain ownerless; name the principal being removed. |
| Bulk sensitivity-label change | admin | Dry-run: show the affected items and before/after label, get confirmation. No service principal / managed identity — the call will fail. |
| Write a tenant setting | admin | Read and show the current value, then the proposed value — tenant-wide blast radius. |
| Assign / unassign one workspace to a domain | dataowner | A move is a reassignment — confirm the current domainId and name the domain it leaves. Needs domain contributor and workspace Admin; say which is missing on failure. |
| Reassign item ownership (item identity, preview) | dataowner | Assigns to the caller only; needs Write on the item and its children. Confirm the intended identity. |
| Assign a workspace to a capacity | dataowner | Needs workspace Admin plus capacity Contributor/Admin. 202 is not success — poll to a terminal state. |
| Apply / remove a workspace tag (preview) | dataowner | Needs workspace Admin. Name the workspace and the tags, and confirm. Removing an applied tag is not deleting its definition. |
Don't promise a write that has no API. Endorsement, DLP policies, an owner changing a sensitivity label, and tenant-admin item deletion have no write route — say so and name who can act (no-write-api-escalation.md). A SQL Database's display name is fixed at creation: never send a rename for it, even when the owner asks for one — say it can't be renamed and offer the description and tags instead.
Shared essentials (all modes)
Prerequisites: auth & tokens · REST, pagination, LRO, rate limits · CLI auth recipes ·
az rest(always pass--resource) · OneLake viacurl(Storage-audience token) · OneLake shortcuts.Resolve workspace and item IDs with the one-call lookups in CRITICAL NOTES 1–2.
Keep tool calls few. Each call re-sends the whole conversation, so extra calls are slow and costly. Combine related reads in one script, and don't re-open a doc you've already read.
Read an item's definition in one command that waits for the long-running operation itself (a semantic model usually returns
202) — never poll it in separate calls. It waits as long as Fabric'sRetry-Afterasks (often 20–30 s), so give the command up to 3 minutes: if your shell tool has a wait or timeout setting, raise it rather than letting the command move to the background. Only for types with a definition: Warehouse, SQL Database, SQL analytics endpoint, ML model/experiment and Datamart have none — read their schema instead. PowerShell 7 (bash:fabric_lroin COMMON-CLI.md):$h = @{ Authorization = "Bearer $(az account get-access-token --resource https://api.fabric.microsoft.com --query accessToken -o tsv)"; 'x-ms-fabric-skill' = 'onelake-catalog-cli' } $st = @{ n = 0; end = (Get-Date).AddMinutes(3) } # Waits the full Retry-After (202 and 429); backs off 2-30 s only when the header is missing or invalid. function Wait-RetryAfter($r) { $ra = 0 if (-not [int]::TryParse("$(@($r.Headers['Retry-After'])[0])", [ref]$ra) -or $ra -lt 1) { $ra = [Math]::Min(30, [Math]::Pow(2, ++$st.n)) } if ((Get-Date).AddSeconds($ra) -gt $st.end) { throw "Definition read did not finish within 3 minutes." } Start-Sleep -Seconds $ra } while (($r = Invoke-WebRequest -Method Post -Uri "https://api.fabric.microsoft.com/v1/workspaces/$WS_ID/items/$ITEM_ID/getDefinition" -Headers $h -SkipHttpErrorCheck).StatusCode -eq 429) { Wait-RetryAfter $r } if ($r.StatusCode -ge 400) { throw "getDefinition returned $($r.StatusCode): $($r.Content)" } $def = if ($r.StatusCode -eq 202) { $op = [string]$r.Headers['Location']; $res = $r; $s = '' while ($s -notin 'Succeeded', 'Failed') { Wait-RetryAfter $res; $res = Invoke-WebRequest $op -Headers $h -SkipHttpErrorCheck if ($res.StatusCode -eq 200) { $s = ($res.Content | ConvertFrom-Json).status } elseif ($res.StatusCode -ne 429) { throw "Polling returned $($res.StatusCode): $($res.Content)" } } if ($s -ne 'Succeeded') { throw "Definition read failed: $($res.Content)" } while (($res = Invoke-WebRequest "$op/result" -Headers $h -SkipHttpErrorCheck).StatusCode -eq 429) { Wait-RetryAfter $res } if ($res.StatusCode -ge 400) { throw "Definition result returned $($res.StatusCode): $($res.Content)" } $res.Content | ConvertFrom-Json } else { $r.Content | ConvertFrom-Json } $dir = New-Item -ItemType Directory -Force -Path (Join-Path ([IO.Path]::GetTempPath()) "def-$ITEM_ID") foreach ($p in $def.definition.parts) { $t = [Text.Encoding]::UTF8.GetString([Convert]::FromBase64String($p.payload)); $f = Join-Path $dir ($p.path -replace '[\\/:]', '_'); Set-Content -LiteralPath $f -Value $t "== $($p.path) ($($t.Length) chars)"; if ($t.Length -le 4000) { $t } else { $t.Substring(0, 4000); "[first 4000 of $($t.Length) chars; full text in $f]" } }A part cut at 4,000 characters is saved in full: read the rest (one call) if what's shown isn't enough.
Use the exact Fabric Admin, Core, Power BI, Graph or OneLake API surface the mode documents; a
401or403is never permission to bypass RBAC.
Rules
MUST
Load exactly one mode reference for the request and follow it end to end; come back to the index below when another procedure is needed. In curate, also read the suggestion guidance before drafting anything, and the table metadata reference before any table or column work.
(curate) Propose exactly what the owner asked for. A specific request gets only that: "add a description" → the item description; "suggest tags" → tags; "describe the table" → the table description only; "describe the columns" → column descriptions only; "describe the item's objects" or "its tables and columns" → both. A general request ("curate this item", "make it more discoverable", "improve its metadata") gets the item's description, name and tags; an item with a OneLake Tables folder also gets its table and column descriptions. If the owner names several items, cover each one, and report each with only the fields it has.
(curate) Check the scope before any call. Curate covers one item, an explicit list of items, or one named workspace at a time. For a tenant-wide request ("all my items", "every workspace"), say plainly that it isn't supported and offer one named workspace or an explicit list; for several named workspaces, ask which to start with. Don't list workspaces or items first.
(govern) State scope, exclusions, pagination completeness, and freshness caveats with every governance statistic.
PREFER
Least-privileged Core or Power BI APIs for data-owner actions instead of requiring tenant-admin rights.
Findings as evidence, consequence, recommended action, priority and effort — not an inventory dump.
Sequencing ownership and access-scope fixes before bulk assignment or labeling.
AVOID
Mutating a tenant from an audit mode, or reporting an asynchronous
202as completion.Inventing write APIs for endorsement, DLP policy, admin item deletion, or third-party item-identity assignment.
(curate) Volunteering anything about table or column descriptions for items without a OneLake Tables folder (semantic models, reports, notebooks, pipelines, dataflows, …). For these items, description, name and tags are the complete list — present them without qualifiers in the preview and whenever you say what the skill can do (e.g. while declining a request, or offering what else you could review next). Don't add a note that table or column descriptions are N/A, don't apply or aren't covered, and don't offer them: the owner didn't ask. Only if they ask, answer that they aren't supported for that item type, then stop and let the owner choose — don't load another skill or draft those descriptions yourself.
(curate) Saying "sub-items" — use the owner's words: "tables" and "columns", or "objects" when speaking generally.
References
Each reference is one hop from this index; after loading one, return here when another is needed.
Curate
Curate — workflow, permission per change, preview format, examples, errors
Suggestion guidance — drafting descriptions, names and tags from content
Tag taxonomy — tenant/domain tag scope and name → ID resolution
Table metadata — table and column descriptions (OneLake table API, preview)
Curation API reference — Update Item, Apply/Unapply Tags, List Tags
Govern — shared
Govern pillars — the three pillars, what "good" looks like, reporting conventions
Governance data sources — verified API field coverage and blind spots
Governance roles — permission tiers, domain/workspace roles, insight refresh lag
Catalog concepts — the entity model and API-backed versus conceptual terms
Govern — modes
Admin audit — tenant-wide read-only governance assessment
Admin audit scope — governable denominator (active workspaces of type Workspace), exclusions, and known blind spots
Admin audit assessment — end-to-end evaluative workflow, prioritization, and deliverable contract
Admin remediate — tenant-wide guarded writes through Admin APIs
Data-owner audit — caller-scoped read-only checks through Core APIs, including a workspace's domain assignment
Data-owner workspace health — empty and inactive workspaces within the caller's scope
Data-owner remediate — least-privileged Core and Power BI writes: moving one workspace to a domain, capacity, workspace tags, refresh, item identity
Govern — admin audit procedures: domain health · workspace health · capacity health · item inventory · item health · protect coverage · trust curation
Govern — admin remediation procedures: domain lifecycle · bulk workspace assignment (tenant admin) · domain roles · tag definitions · item sensitivity labels · domain default labels · trust remediation · no-write escalation
Examples
I'm curating my items for the OneLake catalog. Propose a better description for the semantic model Sales Model in the Finance workspace.Make the lakehouse LSEGDemo more discoverable — describe its tables and columns too.Audit our tenant's OneLake catalog governance posture and prioritize the findings.Which workspaces I administer are not assigned to a domain?Show a dry run for assigning these workspaces to the Finance domain, including current assignments.Find unlabeled items tenant-wide and explain which remediations require a tenant admin versus a data owner.Files
- ATTRIBUTION.mdAdded by AutoGineer883 B
- LICENSELicence file added by AutoGineer1.1 KiB
- SKILL.md21.5 KiB
- apm.yml345 B
- references/admin-audit-assessment.md10.9 KiB
- references/admin-audit-scope.md5.7 KiB
- references/admin-audit.md14.9 KiB
- references/admin-audit/health-capacity.md7.3 KiB
- references/admin-audit/health-domains.md11.5 KiB
- references/admin-audit/health-item.md13.7 KiB
- references/admin-audit/health-workspaces.md15.4 KiB
- references/admin-audit/item-inventory.md9.1 KiB
- references/admin-audit/protect-labels-dlp.md1.4 KiB
- references/admin-audit/trust-curation.md2.8 KiB
- references/admin-remediate.md17.1 KiB
- references/admin-remediate/domain-assign-workspaces.md7.3 KiB
- references/admin-remediate/domain-crud.md10.5 KiB
- references/admin-remediate/domain-default-label.md2.6 KiB
- references/admin-remediate/domain-roles.md4.5 KiB
- references/admin-remediate/item-sensitivity-label.md2.6 KiB
- references/admin-remediate/no-write-api-escalation.md13.4 KiB
- references/admin-remediate/tags.md1.9 KiB
- references/admin-remediate/trust-curate.md3.4 KiB
- references/catalog-concepts.md7.2 KiB
- references/curate.md19.7 KiB
- references/curate/api-reference.md7.8 KiB
- references/curate/metadata-suggestion-guidance.md10.6 KiB
- references/curate/table-metadata.md9.9 KiB
- references/curate/tag-taxonomy.md3.1 KiB
- references/dataowner-audit.md14.4 KiB
- references/dataowner-audit/health-workspaces.md14.1 KiB
- references/dataowner-remediate.md15.0 KiB
- references/govern-data-sources.md7.9 KiB
- references/govern-pillars.md13.3 KiB
- references/govern-roles.md9.9 KiB
references/curate/metadata-suggestion-guidance.md
Metadata Suggestion Guidance
How to turn an item's real content into high-quality, discoverable metadata.
Contents
Principle: ground every suggestion in content
Description formula (high-level & durable, ≤ 256 characters)
Validate an existing description against content
Display name suggestions
Tag suggestions
Table and column descriptions
Owner language
Principle: ground every suggestion in content
Never invent facts about an item. Base each suggestion on signals actually retrieved:
| Signal | Source |
|---|---|
| Item type & display name | GET /v1/workspaces/{ws}/items/{id} |
| Item definition (structure, queries, model) | POST .../items/{id}/getDefinition — not for Warehouse, SQL Database, SQL analytics endpoint, ML model/experiment or Datamart, which have none |
| Tables & schema (OneLake tabular items: Lakehouse, Warehouse, SQL Database, Mirrored Database, KQL) | list-tables (GET .../lakehouses/{id}/tables), SQL analytics endpoint INFORMATION_SCHEMA, or Kusto .show tables (KQL) |
| Existing description / tags | GET items/{id} (validate against content first; preserve & improve if backed by content, flag if contradicted/empty — don't discard, but don't trust blindly) |
| Data sources | GET .../items/{id}/connections |
If a signal is unavailable, do not guess — reduce the suggestion's specificity and note it.
Description formula (high-level & durable, ≤ 256 characters)
An owner description is durable metadata: it should stay accurate over the long run, so keep it high-level — say what the item contains and what it's for, not its current shape. A good description answers two things:
Subject / contents — what real-world entity, domain, or data the item holds.
Purpose — what it's used for (who consumes it and for what analysis).
Template: <Item type> holding <subject/contents> for <durable purpose>.
Examples
Sales Lakehouse containing public holiday reference data by country/region, used for holiday-aware sales and calendar analysis.Customer dimension holding conformed customer attributes (segment, geography), used as the shared customer lookup for BI.
Durability test: would the description still be accurate if a column is renamed, a table is added, or the refresh cadence changes? If not, it's too specific — raise it to a higher level.
Rules
Stay high-level; length is not the goal, durability is (a sentence or two is fine).
Avoid volatile specifics — column names, exact table/row counts, refresh cadence, table grain, or detailed schema shape. Those belong in a point-in-time summary, not in durable owner metadata.
Hard limit 256 chars (Update Item constraint). Trim before proposing.
No marketing language; be specific about what it is, general about its shape.
If the current description is non-empty, offer to improve/merge, not overwrite.
Validate an existing description against content — don't trust it blindly
A non-empty description is a claim to verify, not a fact to preserve. Before deciding to keep ("leave-alone / improve") an existing description, check it against the item's real content signal. Description quality is content-relative — "is it non-empty?" is the wrong test.
Backed by content — the description matches what
getDefinition/ schema actually shows → keep it; offer to improve/merge, don't overwrite.Contradicted or unsubstantiated by content — the description asserts contents or behavior the item does not have (e.g. an empty DataPipeline with
activities: []whose description claims it "ingests source data into the bronze layer") → the description is not representative (stale, aspirational, or copied). Do not silently keep it: flag the mismatch and let the owner decide (the item may be a placeholder the content is coming to, or the description may simply be wrong).Partially configured / incomplete — the item has some real content but isn't fully wired up (e.g. an Eventstream with a source but no destination and no transformations, or a pipeline with one activity and no sink). Describe only what actually exists and explicitly note what's missing ("…no destinations or transformations are configured yet") so the catalog doesn't over-promise end-to-end behavior the item can't yet deliver. Don't infer the finished pipeline from a half-built one.
Empty item, no content signal at all — nothing can be truthfully inferred, so no description can be validated. If one exists, mark it unverified against content; if none exists, say no description can be written yet — never fabricate one from an empty definition.
An empty item can never have a "good" description in the sense of representing its contents — it has none. Treat an existing description as evidence to check, not authority to trust.
Remediation for a contradicted / empty item — offer to remove, not just flag
Misleading metadata is worse than none. A catalog consumer searching OneLake will find the item by its description and tags and expect data or behavior that isn't there — false anticipation. So when content is empty and the description/tags claim otherwise, don't stop at flagging: proactively suggest removing the unsubstantiated metadata (write-gated — the owner confirms). Present it as the owner's choice between two readings:
Placeholder, real content is coming → keep the metadata as forward-looking intent (the owner accepts the mismatch knowingly).
Stale / misleading, no content planned → clear the description (
PATCHwith"description": "") and remove the tags (POST .../unapplyTagswith the tag IDs) so the item stops surfacing false promises to other users.
The display name stays either way (it's required and can't be blanked) — propose no rename on an empty item, just note it's unverified. Never remove metadata without explicit confirmation.
Type-specific note: a Report's description propagates to Power BI
Setting a Report item's description via Update Item also updates the underlying Power BI
report object's description (visible through the Power BI REST API, token audience
https://analysis.windows.net/powerbi/api). One PATCH on the Fabric item updates both the
catalog entry and the Power BI object — no separate Power BI call is needed to keep them in sync.
Display name suggestions
First, check whether the item type even allows a rename. Some types have an immutable display
name — notably SQLDatabase, whose name is fixed at creation (Update Item returns
400 SQLDatabaseDisplayNameCannotBeChanged). For those, do not propose a rename; say it
can't be renamed and let the description carry the meaning. Only if the name is writable, evaluate it on
the two axes below:
Weak / placeholder — the name is cryptic or auto-generated (
lh_tmp2,Untitled,Lakehouse 1, GUID-like). Propose a readable, convention-consistent rename.Content-mismatched — the name looks well-formed but doesn't reflect what the item actually contains (e.g.,
SalesLakehousethat currently holds only a public-holidays reference table). Do not stay silent just because the name isn't a placeholder, and do not rename automatically — the mismatch may be intentional. Instead flag it and let the owner's intent decide, presenting both readings:If the item really is (and will stay) that content → the name misleads; propose a rename that matches the contents (e.g.,
Public Holidays/HolidaysReferenceLakehouse) so people can find and understand it.If the current content is just a seed and the named subject is coming (e.g., a sales lakehouse seeded with a holiday table) → keep the name — it's durable and forward-looking — and let the description carry the point-in-time nuance. Renaming to match today's contents would be wrong the moment the intended data lands.
Always show current → proposed and require confirmation; never rename silently. When it's a content-mismatch, ask the owner which reading is true rather than guessing.
Tag suggestions
Derive 2–5 candidate tags from subject area, data domain, sensitivity theme, and lifecycle (see
tag-taxonomy.md).Map each candidate to an existing applicable tag from
GET /v1/tags: any tenant-scoped tag, or a domain-scoped tag whosescope.domainIdmatches the workspace's current domain. Apply Tags takes tag IDs, not names.A candidate found only in another domain is not applicable and must be excluded. A candidate with no definition can't be applied: say the appropriate Fabric or domain admin would need to create it, and exclude it from
applyTags.
Table and column descriptions
Tables and columns get descriptions only — tags exist only on items. The rules for item descriptions still apply (ground in content, validate existing text, never fabricate), with a different level of detail:
Table — what the table holds and what it is used for, in plain business language. A sentence or two. Template:
<What the table holds> used for <purpose>.e.g.Taxi trips with pickup, drop-off and fare details, used for trip volume, fare, and route analysis.Avoid technical phrasing such as "one row per".Column — what the value means, plus units or allowed codes when the name doesn't make it obvious. One short sentence. e.g.
Total amount charged to the passenger, in US dollars.Ground suggestions in column names and types only. Never read rows, and never put sample values, ranges, counts, or statistics in a description.
Propose only for tables and columns whose description is empty or doesn't match the schema; report the ones that are already fine. Skip columns whose meaning you can't infer from the name and type — list them for the owner to describe.
Column names are fine to mention in a table description when they define the table's key; the item-level "no column names" rule is about the item description only.
Owner language
Show suggestions in the preview's Proposed column and report results as Saved, Skipped or Not
saved. Don't use bracket tags such as [DATA], [INFERENCE] or [GAP]: say in plain words
what can't be done, why, and who can act.
Requirements and compatibility
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
Security
No issues found by our static scan· No issues found
A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.
Attribution and licence
- Published by
- Microsoft
- Publisher
- Microsoft (Official)
- Source
- microsoft/skills-for-fabric · skills/onelake-catalog-cli · commit f8fac11
- Licence
- MIT License (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
- Also distributed in
- microsoft/skills-for-fabric
AutoGineer is not affiliated with or endorsed by Microsoft or Microsoft.
Download ZIP
The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download onelake-catalog-cli.zip