metabase-cli

Drive a Metabase instance from the terminal via the `mb` CLI. Authenticate with named profiles; inspect databases (list, get, full metadata rollup, schemas, tables in a schema) and trigger manual schema sync / field-values rescan; inspect tables, fields; list/get/create/update/archive cards (questions, models, metrics) and run them as JSON/CSV/XLSX; list/get/create/update dashboards and patch dashcards; list/get/create collections and traverse the hierarchy by id, entity_id, or "root"/"trash" (with items and recursive tree); list/get/create/update/archive native query snippets, segments, and measures; author/update/run transforms and schedule transform-jobs; read/update settings; search content (cards, dashboards, collections, transforms, metrics); manage Enterprise workspaces; git-sync to/from a git remote (status, dirty, import, export, branches, stash, add/remove a collection from sync). Use whenever the user wants to interact with a Metabase from the terminal — "log into metabase", "what profiles do I hav

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Repository: metabase/agent-skills
Last source activity: May 15, 2026 at 23:53
Detected SKILL.md language: English
Stars: 45
Forks: 4

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name: metabase-cli
description: Drive a Metabase instance from the terminal via the `mb` CLI. Authenticate with named profiles; inspect databases (list, get, full metadata rollup, schemas, tables in a schema) and trigger manual schema sync / field-values rescan; inspect tables, fields; list/get/create/update/archive cards (questions, models, metrics) and run them as JSON/CSV/XLSX; list/get/create/update dashboards and patch dashcards; list/get/create collections and traverse the hierarchy by id, entity_id, or "root"/"trash" (with items and recursive tree); list/get/create/update/archive native query snippets, segments, and measures; author/update/run transforms and schedule transform-jobs; read/update settings; search content (cards, dashboards, collections, transforms, metrics); manage Enterprise workspaces; git-sync to/from a git remote (status, dirty, import, export, branches, stash, add/remove a collection from sync). Use whenever the user wants to interact with a Metabase from the terminal — "log into metabase", "what profiles do I have", "list cards", "run card 42 as CSV", "create a transform", "list dashboards", "move a dashcard", "list collections", "what's in collection 4", "show the collection tree", "list snippets", "create a segment", "archive a measure", "search metabase for X", "spin up a workspace", "import the latest changes", "add a directory to git sync", "set a setting", "what schemas are in this database", "trigger a sync", "rescan field values", or anything hitting `mb <verb>`.
allowed-tools: Bash(mb:*), Read, Write, Edit, AskUserQuestion

# metabase-cli Load the workflow content from the CLI: ```bash mb skills get core # start here — auth, flag conventions, every command group mb skills list # enumerate specialized skills bundled with this CLI version mb skills get <name> # load a specialized skill (workspace, transform, git-sync, …) ``` Don't drive Metabase by `curl`ing `/api/...` directly — the CLI handles auth profiles, retries, schema validation, and credential redaction.

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ai-governance-checklist

A Metabase AI-governance coach, covering the *controls and rollout* side of AI: who may use Metabot, what it can see, what it costs, where the model runs, and the audit trail. Use this skill whenever the user wants to roll out AI analytics safely, control who can use Metabot or what it can see, set spend or token limits on AI, restrict Metabot's system prompt, audit AI usage, evaluate bring-your-own model or self-hosting options for AI, or prep for a security review of AI features. Trigger it even if the user just says "how do we control AI access", "can we limit what Metabot sees", "we need an AI security review", or "run the AI governance checklist" in a Metabase context. **Not this skill** if the question is about whether the underlying data is modeled, documented, and trustworthy enough for AI — Transforms, metadata, the Glossary, Metrics, the Library — that's `ai-readiness-checklist`. Rough test: this skill is about who gets to point AI at the data; that one is about whether the data is good enough.

2026-08-26

ai-readiness-checklist

A Metabase AI-readiness coach, covering the *data groundwork* that makes AI answers trustworthy: modeling with Transforms, table and field metadata, the Glossary, saved Metrics, and marking canonical content. Use this skill whenever the user wants to check if their data is ready for AI, prep the underlying data for Metabot or the Metabase MCP server, work through an AI readiness checklist, or audit their data modeling/metadata/metrics before turning on AI features. Trigger it even if the user just says "is my data AI ready?", "let's get set up for Metabot", or "run the AI readiness checklist" in a Metabase context. **Not this skill** if the question is about controlling who may use AI, capping AI spend, restricting what Metabot can see, auditing AI usage, or passing a security review — that's `ai-governance-checklist`. Rough test: this skill is about whether the data is good enough; that one is about who gets to point AI at it.

2026-08-26

metabase-learning

A spaced repetition learning coach for Metabase. Use this skill whenever the user wants to: learn Metabase, start a Metabase training session, do a Metabase review, practice Metabase concepts, check what they should study today, get quizzed on Metabase, run through active recall on BI tools, or follow a structured learning program for data analytics software. Trigger this skill even if the user just says "let's do my Metabase session", "quiz me on Metabase", or "what should I study today?" in a Metabase learning context.

2026-06-05

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