What is databricks-aibi-dashboards?

A specialized agent for creating Databricks AI/BI dashboards, which present data through charts and other interactive views.

Use it to inspect table schemas, write and test SQL, and assemble dashboards from queries that have passed validation.

It checks every SQL query before deployment, helping prevent dashboards from being built on invalid queries, wrong columns, or incorrect data types.

How alessandro9110/Speech-To-Text-With-Databricks configures Claude Co

Reuse

Borrowing it

Nothing to install: this file belongs to alessandro9110/Speech-To-Text-With-Databricks. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file

curl -O https://raw.githubusercontent.com/alessandro9110/Speech-To-Text-With-Databricks/main/.github/agents/databricks-aibi-dashboards.agent.md

Clone the repo

git clone --depth 1 https://github.com/alessandro9110/Speech-To-Text-With-Databricks

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/agents/alessandro9110/speech-to-text-with-databricks/databricks-aibi-dashboards/github.svg)](https://agentmods.dev/agents/alessandro9110/speech-to-text-with-databricks/databricks-aibi-dashboards)

Your own site

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Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/agents/alessandro9110/speech-to-text-with-databricks/databricks-aibi-dashboards"><img src="https://agentmods.dev/badge/agents/alessandro9110/speech-to-text-with-databricks/databricks-aibi-dashboards.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 37 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.

When invoked 5,047 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00037	$0.05047
Opus 5.5	$0.00015	$0.02019
Sonnet 5.5	$0.00007	$0.01009
Haiku 4.5	$0.00004	$0.00505

Measured 1mo ago against content hash f6403e470f02, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

databricks-aibi-dashboards scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.github/agents/databricks-aibi-dashboards.agent.md · 534 lines

How it starts

The opening of the file, as written. The whole thing — 534 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are a specialized GitHub Copilot agent for Databricks. Use the knowledge below to assist with tasks.

AI/BI Dashboard Skill

Create Databricks AI/BI dashboards (formerly Lakeview dashboards). Follow these guidelines strictly.

CRITICAL: MANDATORY VALIDATION WORKFLOW

You MUST follow this workflow exactly. Skipping validation causes broken dashboards.

┌─────────────────────────────────────────────────────────────────────┐
│  STEP 1: Get table schemas via get_table_details(catalog, schema)  │
├─────────────────────────────────────────────────────────────────────┤
│  STEP 2: Write SQL queries for each dataset                        │
├─────────────────────────────────────────────────────────────────────┤
│  STEP 3: TEST EVERY QUERY via execute_sql() ← DO NOT SKIP!         │
│          - If query fails, FIX IT before proceeding                │
│          - Verify column names match what widgets will reference   │
│          - Verify data types are correct (dates, numbers, strings) │
├─────────────────────────────────────────────────────────────────────┤
│  STEP 4: Build dashboard JSON using ONLY verified queries          │
├─────────────────────────────────────────────────────────────────────┤
│  STEP 5: Deploy via create_or_update_dashboard()                   │
└─────────────────────────────────────────────────────────────────────┘

WARNING: If you deploy without testing queries, widgets WILL show "Invalid widget definition" errors!

Available MCP Tools

Tool	Description
`get_table_details`	STEP 1: Get table schemas for designing queries
`execute_sql`	STEP 3: Test SQL queries - MANDATORY before deployment!
`get_best_warehouse`	Get available warehouse ID
`create_or_update_dashboard`	STEP 5: Deploy dashboard JSON (only after validation!)
`get_dashboard`	Get dashboard details by ID, or list all dashboards (omit dashboard_id)
`delete_dashboard`	Move dashboard to trash
`publish_dashboard`	Publish (`publish=True`) or unpublish (`publish=False`) a dashboard

Read the full file on GitHub · 534 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

1mo ago First seen · 534 lines · 37 tokens per session scan A f6403e470f02

Subscribe to this mod's changes

databricks-aibi-dashboards is an agent published in the GitHub repository alessandro9110/Speech-To-Text-With-Databricks (4 stars, last pushed 8mo ago), licensed MIT. It adds 37 tokens to every session and 5,047 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-02.

Analytics and metrics databricks delta-lake generative-ai lakehouse machine speech-to-text

databricks-aibi-dashboards next to 6 agents from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
databricks-aibi-dashboardsalessandro9110/Speech-To-Text-With-Databricks	Agent	4	8mo ago	MIT	A	37	Claude Code
reviewerirahardianto/awesome-agv	Agent	158	23d ago	MIT	A	51	Claude Code
integration-proberirahardianto/awesome-agv	Agent	158	23d ago	MIT	A	49	Claude Code
designerpjt222/agent-almanac	Agent	43	yesterday	MIT	A	29	Claude Code
architectirahardianto/awesome-agv	Agent	158	23d ago	MIT	A	48	Claude Code
database-expertirahardianto/awesome-agv	Agent	158	23d ago	MIT	A	37	Claude Code
backend-engineerirahardianto/awesome-agv	Agent	158	23d ago	MIT	A	41	Claude Code

Speech-To-Text-With-Databricks: Agent for Claude Code