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Eventschemaset Cli

OrganizationPopular
microsoft
eventschemaset-cli

Governs Event Schema Sets, the Fabric registries of event types and message payload schemas. Covers create, rename, update and delete of a definition, and listing, property reads or base64 decoding. Every Event Schema Set task belongs here. Ingestion pipelines are eventstream-cli.

Overview

Publishermicrosoft
Repositoryskills-for-fabric
Skill nameeventschemaset-cli
Stars
1.2K
Forks
354
Bundled files
2
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by microsoft on GitHub. Read the source before you install it.

Installation

Install the Eventschemaset Cli AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/microsoft/skills-for-fabric/tree/main/plugins/fabric-skills/skills/eventschemaset-cli
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/microsoft/skills-for-fabric.git /tmp/skills-for-fabric
mkdir -p .claude/skills
cp -r /tmp/skills-for-fabric/plugins/fabric-skills/skills/eventschemaset-cli .claude/skills/eventschemaset-cli
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Eventschemaset Cli in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Eventschemaset Cli on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Eventschemaset Cli is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Telemetry — MANDATORY. Every api.fabric.microsoft.com call must carry x-ms-fabric-skill: eventschemaset-cli (az rest: --headers "x-ms-fabric-skill=eventschemaset-cli"), including every LRO poll, fabric_lro and retry. Snippets omit it — add it anyway.

CRITICAL NOTES

  1. To find the workspace details (including its ID) from workspace name: list all workspaces and, then, use JMESPath filtering
  2. 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
  3. Skill disambiguation: use eventschemaset-cli for the EventSchemaSet catalog item (event types and message schemas). Eventstream is a different item -- a real-time ingestion and routing pipeline; use eventstream-cli for it. Eventhouse / KQL Database is another different item; use eventhouse-cli for it.

Fabric Event Schema Set -- CLI Skill

This one skill owns Fabric Event Schema Sets: authoring the catalog (create, rename, override definition, delete) plus read-only inspection and decoding of its eventTypes and schemas.

Preview: The Fabric EventSchemaSet item and its REST operations are currently in Preview -- behavior, response shapes, and availability may change. Every operation is documented as delegated (user) identity only (service principals and managed identities listed as not supported), but because the item is in Preview, SP/MI access can succeed and is tenant-dependent. Prefer az login as a user; on 401/403 with an SP/MI, fall back to a delegated user identity.

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

ModeUse when the request ...Example triggersRead this first
authoringcreates, renames/re-describes, overrides the definition of, or deletes an Event Schema Set (Create, Update, UpdateDefinition, Delete)create event schema set, update event schema set definition, add event type to an event schema set, rename event schema set, delete event schema setreferences/authoring.md
consumptionlists or searches Event Schema Sets, inspects item properties, or decodes a definition to enumerate its eventTypes and schemaslist event schema sets, inspect event schema set, decode event schema set definition, get schema version, list business eventsreferences/consumption.md

Mode boundary rule

consumption may only issue read-only calls (List, Get, GetDefinition). Any state-changing operation (Create, Update, UpdateDefinition, Delete) requires the authoring mode: say so, read references/authoring.md, then proceed.

If a request genuinely spans modes (e.g. decode the current definition, then override it), 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 planning the change is NOT completing the task. The authoring mode ends with one state-changing call. If you did not issue it, nothing was persisted -- say so explicitly rather than reporting success.

ModeTerminal write
authoringThe POST .../eventSchemaSets, PATCH .../eventSchemaSets/{id}, POST .../eventSchemaSets/{id}/updateDefinition, or DELETE .../eventSchemaSets/{id} for the requested change. Composing the request body and showing it to the user is not executing it.
consumptionnone -- this mode is read-only

Create and UpdateDefinition may return 202 Accepted (LRO): capture the Location header and poll until Succeeded before reporting success. Where the reference documents a readback, read the artefact back to prove the change landed.

Shared essentials (all modes)

Resolve the workspace and item first; every mode depends on it.

TaskReferenceNotes
Finding Workspaces and Items in FabricCOMMON-CLI.mdMandatory -- read before resolving any workspace or item id
Fabric Topology & Key ConceptsCOMMON-CORE.mdItem types, workspaces, capacities
Environment URLsCOMMON-CORE.mdSovereign / non-public cloud hosts
Authentication & Token AcquisitionCOMMON-CORE.mdWrong audience = 401; read before any auth issue
Authentication RecipesCOMMON-CLI.mdaz login flows and token acquisition
Core Control-Plane REST APIsCOMMON-CORE.mdPagination, LRO polling, rate limiting
Gotchas & TroubleshootingCOMMON-CLI.mdaz 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.
  • Apply the same read-once discipline to every other file you load, including shared common/*.md files: open only the ones you actually need, read each ONCE end to end, and never grep or re-open one you already loaded.
  • Resolve workspace and item ids by listing and filtering, never by guessing a GUID.
  • Announce a mode switch explicitly when the request crosses a boundary.
  • Confirm destructive and overwrite actions before executing -- Delete is permanent (with ?hardDelete=true) and UpdateDefinition replaces the whole definition. When the request already names the target item AND the destructive/overwrite action explicitly (e.g. "delete the Event Schema Set X", "override X's definition to ..."), that instruction IS the confirmation: echo the resolved displayName + id for the audit trail, then proceed with the single write. Pause for a separate yes/no confirmation ONLY when the target or intent is ambiguous (e.g. "clean up my workspace", an unqualified "the first one", or a bulk/wildcard delete).
  • Treat the reference as instructions, never as the deliverable. After reading it, RUN the documented commands against the live workspace and report the real results.

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.
  • A delegated user identity (az login); fall back from SP/MI to a user on 401/403.
  • Reporting the mode you chose in your first response so the user can correct you.

AVOID

  • Acting from this dispatcher alone -- it intentionally omits the operational detail.
  • 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 the read-only consumption mode.
  • Confusing EventSchemaSet with Eventstream or Eventhouse (see CRITICAL NOTES 3).

Examples

User requestModeReference to read
"List all Event Schema Sets in my Analytics workspace."consumptionreferences/consumption.md
"Create an Event Schema Set called orders-catalog in Analytics."authoringreferences/authoring.md
"Decode the definition of orders-catalog and tell me its event types and schemas."consumptionreferences/consumption.md
"Add a BusinessEventType event OrderPlaced (JSON) to orders-catalog."authoringreferences/authoring.md
"Delete the orders-catalog-old Event Schema Set from Analytics."authoringreferences/authoring.md

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Eventschemaset Cli AI skill do?

Governs Event Schema Sets, the Fabric registries of event types and message payload schemas. Covers create, rename, update and delete of a definition, and listing, property reads or base64 decoding. Every Event Schema Set task belongs here. Ingestion pipelines are eventstream-cli.

Why use Eventschemaset Cli on TypingMind?

Because you install it once and use it with any model. Eventschemaset Cli is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Eventschemaset Cli in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/microsoft/skills-for-fabric/tree/main/plugins/fabric-skills/skills/eventschemaset-cli. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Eventschemaset Cli?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Eventschemaset Cli?

As many as you like. As long as a model supports skills, you can use Eventschemaset Cli with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Eventschemaset Cli AI skill free?

Yes. It is published on GitHub by microsoft under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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