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通过命令行创作与管理 Fabric Dataflows Gen2，并预览查询和触发刷新。
复制安装指令，让 AI 自动完成配置 · 推荐新手
请帮我安装 askskill 上的 "dataflows-authoring-cli" 技能： 1. 下载 https://raw.githubusercontent.com/microsoft/skills-for-fabric/main/skills/dataflows-authoring-cli/SKILL.md 2. 保存为 ~/.claude/skills/dataflows-authoring-cli/SKILL.md 3. 装好后重载技能，告诉我可以用了
请用 dataflows-authoring-cli 创建一个 Fabric Dataflows Gen2 数据流：先创建到 Azure SQL 的数据源连接，再将连接绑定到数据流，输出目标设置为 Lakehouse，并返回所需命令与参数说明。
一组按顺序执行的 CLI 命令，用于创建连接、绑定连接、创建数据流并配置 Lakehouse 输出。
请用 dataflows-authoring-cli 帮我迭代一个 Power Query M 脚本：使用 executeQuery + customMashupDocument 先预览结果，再根据报错修改 mashup，直到预览成功，并给出最终可保存的定义文件结构。
预览驱动的调试流程、修正后的 M 脚本，以及可用于保存的数据流定义结构说明。
请用 dataflows-authoring-cli 更新现有 Fabric Dataflow 的查询定义和输出目标为 Warehouse，然后触发一次带参数的 refresh，并列出对应命令、参数示例和注意事项。
用于更新数据流、修改输出目标并触发参数化刷新的命令示例与执行说明。
Update Check — ONCE PER SESSION (mandatory) The first time this skill is used in a session, run the check-updates skill before proceeding.
- GitHub Copilot CLI / VS Code: invoke the
check-updatesskill.- Claude Code / Cowork / Cursor / Windsurf / Codex: compare local vs remote package.json version.
- Skip if the check was already performed earlier in this session.
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
This skill (SKILL.md)
| Section | Notes |
|---|---|
| Tool Stack |
az + jq + base64 + curl |
| Connection | Workspace/dataflow ID discovery |
| Agentic Workflows | Start here. A: create end-to-end; B: modify existing; C: preview loop |
| MUST DO / AVOID / PREFER | Authoring rules |
| Troubleshooting | Symptom → fix table |
| Examples | Runnable bash + PowerShell recipes |
| Output Expectations | Response conventions |
References (in references/)
| File | When to read |
|---|---|
| authoring-cli-quickref.md | One-liner recipes, status enums, base64 helpers, connection-binding quick patterns |
| authoring-script-templates.md | Full bash + PowerShell templates; end-to-end smoke test; LRO polling pattern |
| connection-management.md | List/create/inspect connections; supportedConnectionTypes; resolve ClusterId; ID format cheat sheet |
| mashup-preview.md | executeQuery contract: bootstrap branch, auto-wrap rule, hard avoid for unbounded preview |
| output-destinations.md | Output destination patterns: Lakehouse Table, Lakehouse Files, Warehouse, ADX, Azure SQL. DataDestinations annotation, hidden query, loadEnabled rules, connection limitations |
Common refs (in ../../common/)
| File | When to read |
|---|---|
| COMMON-CLI.md | az login, token acquisition, az rest, pagination, LRO polling, CLI gotchas. § Finding Workspaces and Items in Fabric is mandatory. |
| COMMON-CORE.md | Fabric topology, environment URLs, authentication, core REST API surface |
| ITEM-DEFINITIONS-CORE.md | Definition envelope; per-item-type payload contracts |
| DATAFLOWS-AUTHORING-CORE.md | Authoring capability matrix; 3-part definition structure; M structure; connection model; ALM / Git integration |
Sister skills
| Skill | Use for |
|---|---|
| dataflows-consumption-cli | Execute persisted queries; ad-hoc read-only customMashupDocument with no intent to persist; Arrow → CSV/pandas conversion; refresh status/history. |
| Tool | Role | Install |
|---|---|---|
az CLI | Primary: Auth (az login), REST API calls (az rest), token acquisition. | Pre-installed in most dev environments |
jq | Parse and manipulate JSON responses and definition payloads. | Pre-installed or trivial |
base64 | Encode/decode definition parts for the REST API. | Built into bash / [Convert]::ToBase64String() in PowerShell |
curl | Alternative to az rest when raw HTTP control is needed. | Pre-installed |
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