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Meru-Fin-Tech

HelloBooks AI MCP Server

estimate_migration_effort

Analyze a QBO or Xero journal-entry CSV to estimate migration effort, including row counts, complexity, hours, and cost. Use it to determine if migrating books to HelloBooks is worthwhile.

Instructions

Take a QBO or Xero journal-entry CSV (source auto-detected) and return a structured migration-effort estimate — row counts, unique-account count, period span, complexity classification (low / medium / high), human-hours estimate, assisted-hours estimate, and an indicative price quote in USD. Heuristic-based — refined against the live entity once the user signs up. Accepts larger files than the other analytical tools (up to 50,000 rows / 20 MB) because no detection runs here, just sizing. Use this when a user is weighing the cost of moving books to HelloBooks, pastes data and asks "how long will migration take?", "what would this cost?", or "is it worth migrating?". The funnel CTA points at /migrate/?ref= to start the assisted flow with the parsed sizing pre-populated.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
csvTextYesRaw CSV text of a journal-entry export from QBO ("Journal Entries") or Xero ("Manual Journals"). Source is auto-detected from headers.
fileNameNo
Behavior4/5

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

With no annotations, the description fully discloses heuristic nature, refinement after signup, and file size limits (50k rows/20MB). It clarifies this is a sizing-only tool (no detection) and implies it is non-destructive.

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 fairly long but well-structured: front-loaded with core function and outputs, then details file limits, usage context, and CTA. Most sentences add value, though the CTA could be considered extra.

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

Completeness4/5

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

Given no output schema, the description effectively enumerates return fields. It covers input format, source detection, size limits, and typical use cases. Missing details on error handling, but sufficient for correct invocation.

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

Parameters3/5

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

Schema coverage is 50% (csvText described). The description adds meaning for csvText (source auto-detection, expected format) but not for fileName. Overall, it compensates partially for the missing schema detail.

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 specifies a concrete action ('estimate migration effort') on a clear input (QBO/Xero journal CSV) and lists specific outputs (row counts, cost estimate). It differentiates from sibling analytical tools by mentioning larger file acceptance and no detection.

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

Usage Guidelines4/5

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

The description explicitly states when to use (user weighing migration cost, asking cost/time questions) and provides a CTA. It does not explicitly name alternatives but contrasts with 'other analytical tools,' making usage context clear for an agent.

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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