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Meru-Fin-Tech

HelloBooks AI MCP Server

analyze_trial_balance

Analyze a Trial Balance CSV to verify if debits equal credits, detect sign errors, and flag round-number balances that may indicate plug entries. Identifies issues that make downstream financial statements invalid.

Instructions

Take a Trial Balance CSV export from QuickBooks Online, Xero, Zoho Books, or Wave (source auto-detected from headers — YTD columns indicate Xero, Opening Balance indicates Zoho, etc.) and run three checks: (1) tb.unbalanced — debits ≠ credits (every downstream P&L / BS / cash-flow report built from this TB is wrong until fixed); (2) tb.wrong_sign — accounts whose name suggests a class (Revenue / COGS / Expense / AR / AP) carrying a balance on the wrong side (classic posting-error signal); (3) tb.round_balance — exact-multiple-of-$10,000 balances (plug-entry signal). Input is raw CSV text of a Trial Balance report. Max 5,000 rows; max 5 MB. Returns flagged accounts with severity, a roll-up showing whether the TB balances, parse diagnostics, and a shareable URL at agents.hellobooks.ai/r/{slug}. Use this when a user pastes a Trial Balance and asks "does my TB balance?", "are there sign errors?", "what looks suspicious?", or "is this TB clean?". The Trial Balance is the foundation document for every other financial statement — if it does not balance, every downstream report is invalid.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
csvTextYesRaw CSV text of a Trial Balance report. Works with QuickBooks Online (Reports → Trial Balance), Xero (Reports → Trial Balance), Zoho Books (Reports → Accountant → Trial Balance), and Wave (Reports → Trial Balance). Source is auto-detected from column headers.
fileNameNoOptional filename for the share-page label.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.5.0

TDQS

A4.6/5.0
Behavior5/5

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

With no annotations, the description fully discloses behavioral traits: auto-detection of CSV source from headers, max rows/ size limits, the three checks performed, and the returned data (flagged accounts, severity, roll-up, diagnostics, shareable URL). It also warns about downstream report invalidity if the TB is unbalanced.

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 relatively long but well-structured: it starts with the tool's purpose, lists the checks, specifies input constraints, and describes output. Every sentence provides essential information; however, it could be slightly more concise without losing clarity.

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 adequately explains the return values (flagged accounts with severity, roll-up, diagnostics, shareable URL) and input limits. It lacks exact output structure details, but the summary is sufficient for an agent to understand what to expect.

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

Parameters5/5

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

Schema coverage is 100% with descriptions for both parameters. The description adds significant value beyond the schema by explaining how csvText is used (raw CSV from specific sources), the auto-detection logic, the three checks, and that fileName is optional for a share-page label.

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 ('analyze') and resource ('Trial Balance CSV') and clearly distinguishes the tool from sibling tools by detailing the three specific checks (unbalanced, wrong sign, round balance) and listing supported accounting software. No sibling tool covers trial balance validation.

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 the tool: 'when a user pastes a Trial Balance and asks...' and provides example queries. It does not explicitly mention when not to use it or suggest alternative tools for other financial statements, but the context is clear enough for correct selection.

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