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HelloBooks AI Agents MCP Server

by io.github.HelloBooksAIAgents

analyze_xero_journal_anomalies

Scan a Xero "Manual Journals" CSV export for anomalies — currently round-number lines (debit or credit amounts that are exact multiples of $1,000, above a $1,000 materiality threshold). Input is raw CSV text from Xero Accounting → Advanced → Manual Journals → Export. Max 5,000 rows; max 5 MB. Returns flagged lines with severity ($100K+ high, $10K+ medium, else low) and a shareable URL. Use this when a user pastes Xero data and asks "any anomalies?", "look for round numbers", or "anything suspicious". Same Tier-0 / paid-product split as the QBO variant — history-aware anomaly checks (GL outliers, vendor history, archived-vendor activity, LLM-narrated suspicious) live in the authenticated MCP / paid product.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
csvTextYesRaw CSV text of a Xero "Manual Journals" report. Export from Xero: Accounting → Advanced → Manual Journals → Export. Paste the file contents directly.
fileNameNoOptional original filename, used only as a label on the share page.

TDQS

A4.6/5.0
Behavior5/5

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

No annotations provided, but the description fully discloses behavior: anomaly detection rules (round-number lines, $1k threshold), input limits (5k rows, 5MB), output format (flagged lines with severity and shareable URL), and separation from advanced checks. No contradictions.

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 somewhat long but front-loads the main purpose and is logically organized. Every sentence adds useful information; slight trimming could improve conciseness without losing meaning.

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 the moderate complexity and absence of an output schema, the description covers input requirements, processing limits, detection criteria, severity levels, output format, and use-case triggers. No gaps remain.

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?

Description adds value beyond the input schema by noting the specific Xero export path, max row/size limits, and that fileName is used as a label on the share page. Schema coverage is 100%, so baseline is 3; the extra context earns a 4.

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 states the action: 'Scan a Xero Manual Journals CSV export for anomalies' and specifies the resource. It distinguishes from sibling tools by mentioning the QBO variant and the paid product split.

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?

Explicit triggers are given ('any anomalies?', 'look for round numbers', 'anything suspicious') and context about paid product for advanced checks. However, it does not directly mention when not to use it or list alternative tools for specific needs.

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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TDQS

A3.8/5.0
Disambiguation4/5

Tools are largely distinct, each targeting a specific report type (balance sheet, P&L, trial balance) or functionality. Some overlap exists between QBO and Xero variants, but descriptions clearly differentiate them. Overall, an agent can reliably select the right tool.

Naming Consistency4/5

Most tools follow a consistent snake_case verb_noun pattern (e.g., analyze_balance_sheet, list_articles). A few exceptions like free_tier_eligibility and how_munimji_helps break the pattern but are still readable and predictable.

Tool Count3/5

With 29 tools, the count is on the higher side but justified by the domain's breadth (financial analysis, compliance, migration, pricing, etc.). Some reduction through parameterization (e.g., merging QBO/Xero variants) would improve scope.

Completeness4/5

The tool surface covers key areas: financial statement analysis, compliance, migration estimation, feature/pricing info, and partner programs. Missing are direct data manipulation tools (e.g., create/edit journal entries), which may be intentional for a read-only analysis agent.

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