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HelloBooks AI Agents

by ai.hellobooks.agents

list_plans

List HelloBooks pricing plans with monthly + annual prices in 8 regional currencies (USD, INR, CAD, GBP, AUD, AED, SGD, NZD). Covers four core tiers — Free / Pro / Business / Partner Program (the cpa plan id) — plus two per-entity stackable add-ons (Warehouse, Manufacturing). Returns AI credit allowance, feature bullets (AI auto-categorization, unlimited users, multi-entity, 3-way matching, API access, etc.), and the public signup URL. Filter by plan (one of free / pro / business / cpa) or country (ISO code). Pricing follows Doc 19 v3 (Web-Fire #514, 2026-06-12): Business re-introduced as a 4th tier sized ~4× Pro to match Partner Points; the retired "$59.99/mo + $4.99/client" CPA SKU is gone and the cpa plan id now resolves to the free Partner Program (call partner_program_info for the status ladder + points math). HelloCPA Practice Management is a separate product on practice.hellobooks.ai — call practice_management_info, NOT this tool.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
planNoRestrict the response to a single plan tier (`cpa` = free Partner Program).
countryNoISO country code. Filters prices to one country. Omit to return all 8 markets.

TDQS

A4.7/5.0
Behavior4/5

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

With no annotations, the description carries the full burden. It explains that the tool is read-only (listing), mentions pricing history changes, and clarifies the cpa plan id. However, it does not explicitly state that it is non-destructive, which is implicit from 'list'.

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 front-loaded with the core purpose and then provides detailed context. While every sentence adds value, the inclusion of specific pricing history references (Doc 19 v3, Web-Fire #514) is slightly verbose for an AI agent. Still, it is well-structured.

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 no output schema, the description thoroughly explains what the tool returns: currencies, tiers, add-ons, feature bullets, credit allowance, signup URL. It also clarifies the cpa plan id and directs to other tools for related info. This is complete for a listing tool.

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?

The input schema has 100% coverage with descriptions for each parameter. The description adds significant extra meaning: it explains the plan filter values (including the cpa id mapping to free Partner Program), the country ISO codes, and provides context about the pricing tiers.

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 tool's action ('List') and resource ('HelloBooks pricing plans'), specifying monthly+annual prices in 8 currencies, four core tiers plus add-ons, and return fields. It distinguishes itself from similar tools like partner_program_info and practice_management_info.

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

Usage Guidelines5/5

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

The description explicitly tells when to use this tool (to list pricing plans) and when not to (for partner program details or practice management), naming alternatives. It provides clear context for filtering by plan or country.

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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