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Meru-Fin-Tech

HelloBooks AI MCP Server

list_tax_rates

List statutory tax rate slabs for GST, VAT, and sales tax across jurisdictions. Filter by country, tax type, or scheme to find applicable rates with official source URLs.

Instructions

List statutory tax-rate slabs by jurisdiction — IN GST (5/12/18/28 + zero + exempt + composition trader/manufacturer/restaurant + compensation cess), UK VAT (20 / 5 / zero / exempt), AU GST (10 / GST-free), US sales-tax (state-administered summary, no federal rate), CA GST 5% + HST 13% ON / 15% Atlantic, SG GST 9%, NZ GST 15%, AE VAT 5%. Filter by country, taxType (GST/VAT/Sales-Tax/HST/IGST/CGST-SGST/TDS/TCS), or scheme (standard / reduced / zero / exempt / composition / cess / state-summary). Every entry carries an effective-from date and an authoritative source URL (CBIC, gov.uk, ATO, CRA, IRAS, IRD, FTA, Tax Foundation) — agents should confirm the rate against the source before quoting figures to a user. Use this when a user asks "what is the GST rate on X?", "what VAT band does Y fall into?", or "what are the composition slabs in India?". This is the public statutory reference — for an org-specific tax assignment use the authenticated books_classify_event tool.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countryNoFilter to one jurisdiction. Omit to return every supported country.
taxTypeNoFilter by statutory tax type (GST, VAT, Sales-Tax, HST, etc.).
schemeNoFilter by slab category — standard, reduced, zero, exempt, composition, cess.
Behavior4/5

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

No annotations provided, so the description bears full burden. It specifies that each entry carries an effective-from date and source URL, and warns agents to confirm against source. It implies read-only behavior but does not explicitly state auth requirements or rate limits.

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 detailed but well-structured, front-loading the purpose. It could be slightly more concise, but every sentence provides relevant information.

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 adequately explains return fields (effective-from, source) and covers multi-country complexity. Complete for a list tool with 3 optional parameters.

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 covers 100% of parameters with descriptions and enums. The description adds value by providing examples of how to use filters (e.g., 'Filter by country, taxType, or scheme') and specifying the filtering capabilities.

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 it lists statutory tax-rate slabs by jurisdiction, provides specific examples for multiple countries, and distinguishes from sibling tools like lookup_tax_rate and books_classify_event.

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?

Explicitly says when to use (e.g., 'what is the GST rate on X?') and when not to ('for an org-specific tax assignment use the authenticated books_classify_event tool').

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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