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pete-welch-db

Databricks Domo Migration Accelerator MCP Server

migration_plan

Generate a prioritized wave-sequenced plan for migrating Domo assets to Databricks, combining tenant census, dataflow assessment, and Lakeflow Connect feasibility into a structured migration deliverable.

Instructions

Produce the prioritized Domo->Databricks migration plan.

Combines the tenant census, per-dataflow assessment, and per-source Lakeflow Connect feasibility into a wave-sequenced plan ranked by business value then migration complexity. This is the structured "assessment deliverable" a customer engagement produces.

Returns waves, the governance split, source feasibility rollup, and the recommended pilot. All figures are draft-grade until live tenant data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses the output structure (waves, governance split, source feasibility rollup, recommended pilot) and that figures are 'draft-grade'. This adds useful behavioral context beyond a simple 'produce plan'.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the main purpose and then elaborates on inputs and outputs. It is reasonably concise but could be slightly tighter by merging the second and third sentences without loss of clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given zero parameters and an output schema that likely details return fields, the description fully covers what the tool does and what it returns. No missing information is evident for an agent to decide whether to invoke this tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

There are zero parameters, so the description need not add param details. It compensates by explaining what the tool produces and how it combines inputs, which is valuable semantics for an agent with no configurable inputs.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Produce the prioritized Domo->Databricks migration plan') and clearly states the resource (migration plan). It distinguishes from sibling tools like domo_assess and domo_discover by positioning this as the final 'assessment deliverable' that combines multiple inputs.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies this tool is used after census, assessment, and feasibility steps, but does not explicitly state when NOT to use it or provide alternative tools for different scenarios. The context is clear but lacks exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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