HelloBooks AI Agents

local_payment_methods

List local bank-rail / wallet payment methods relevant to HelloBooks invoice collection (AR), B2B supplier payments (AP), and contractor payouts (UPI, RuPay, Razorpay, IMPS, NEFT, RTGS, BACS, FPS, CHAPS, Open Banking, Interac e-Transfer, EFT, PayID, PayTo, NPP, BPAY, ACH, Same Day ACH, Fedwire, RTP, Zelle, PayNow, FAST, GIRO, NZ Direct Credit, etc.). Returns rail (instant / same-day / next-day / multi-day), use-cases, issuing authority, HelloBooks support level, and operational notes (per-transaction caps, settlement windows, retirement timelines). Filter by country, useCase, rail, or id.

Input Schema

TableJSON Schema

Name	Required	Description
`id`	No	Return a single payment method by id (e.g. "in-upi", "au-payid", "us-rtp").
`rail`	No	Filter by settlement rail (instant, same-day, next-day, multi-day).
`country`	No	Filter to one country (IN, US, CA, GB, AU, AE, SG, NZ).
`useCase`	No	Filter by payment use-case. Defaults to HelloBooks' invoice-collection + b2b-supplier + contractor-payout scope; pass an explicit value to widen.

TDQS

A4.4/5.0

Behavior4/5

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

No annotations provided, but description fully discloses what the tool returns (rail types, use-cases, issuing authority, support level, operational notes). It implies read-only behavior without stating it directly.

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?

One paragraph, front-loaded with purpose. Contains a lot of information but is still relatively concise. Could be slightly more structured (e.g., bullet points), but no unnecessary sentences.

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?

No output schema, but description lists what the response contains (rail, use-cases, authority, support, notes). All parameters covered, filtering explained, defaults provided. Complete for a list 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?

Schema has 100% coverage with descriptions. The description adds context: default useCase scope, examples of IDs (e.g., 'in-upi'), and enumerates many payment methods, which adds semantics 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?

Description clearly states it lists local payment methods with specific examples (UPI, RuPay, etc.) and details on what it returns (rail, use-cases, etc.). It is distinct from sibling tools which are analytical/compliance in nature.

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?

Description explicitly states filtering capabilities by country, useCase, rail, or id. It also mentions default scope for useCase and how to widen it. No explicit when-not to use, but siblings are different so context is clear.

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

A3.9/5.0

Disambiguation5/5

Each tool has a clearly distinct purpose, with detailed descriptions that specify the exact input and use case. Even similar tools like QBO vs Xero journal analyzers are differentiated by source system and specific checks, leaving no ambiguity.

Naming Consistency4/5

The majority of tools follow a verb_noun snake_case pattern (e.g., analyze_balance_sheet, list_features). A few exceptions like how_munimji_helps and feature_search deviate slightly, but overall the convention is consistent and readable.

Tool Count4/5

With 26 tools covering financial analysis, compliance, migration, and product info, the count is on the higher side but justified by the breadth of the accounting domain. Each tool serves a specific need without redundancy.

Completeness4/5

The tool set covers all major financial statement checks (balance sheet, P&L, trial balance, journal entries), compliance, migration, and product details. A notable gap is the lack of cash flow analysis, but the set is otherwise comprehensive for its scope.

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