Skip to main content
Glama
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.
Behavior4/5

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

Discloses auto-detection of source, three checks, output types (flagged accounts, roll-up, diagnostics, shareable URL), and constraints (max rows/size). Without annotations, this is thorough, though error handling could be mentioned.

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?

Well-structured with numbered checks and clear output list. Slightly verbose but each sentence adds value; could be slightly tighter.

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?

Describes return values (flags, roll-up, diagnostics, URL) despite no output schema. Covers input and behavior adequately. Missing error handling details.

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?

Schema coverage is 100%, but the description adds value by explaining compatible sources, auto-detection logic, and the optional fileName. This provides meaningful context beyond the schema.

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 clearly defines the tool's purpose: analyzing a Trial Balance CSV from multiple sources by running three specific checks. It distinguishes from sibling tools that handle other financial statements or journal anomalies.

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?

Explicitly lists use cases (e.g., 'does my TB balance?') and emphasizes the foundational importance of the TB. While no explicit 'when not to use' is stated, the sibling context makes it clear.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Meru-Fin-Tech/HelloBooks-MCP-Public'

If you have feedback or need assistance with the MCP directory API, please join our Discord server