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Australian Consumer Data Right Product Data - CDR Explorer

by au.com.cdrexplorer

Get Single Product Lending Rates

get_product_lending_rates
Read-onlyIdempotent

Returns the lending rates of a specific banking product (identified by Product ID) offered by a Data Holder, as defined by the CDR Banking standards (BankingProductLendingRateV2). Use GetDataHoldersByCategory first to obtain a valid Data Holder Brand ID.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
productIdYesThe unique identifier of the product whose features should be retrieved
loanPurposeNoFilter by loan purpose (e.g. OWNER_OCCUPIED, INVESTMENT). Leave empty for all.
repaymentTypeNoFilter by repayment type. (e.g. INTEREST_ONLY, PRINCIPAL_AND_INTEREST). Leave empty for all.
lendingRateTypeNoFilter by lending rate type (e.g. FIXED, VARIABLE). Leave empty for all types.
dataHolderBrandIdYesThe unique brand identifier of the Data Holder, as returned by GetDataHoldersByCategory

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true, covering the safety profile. The description adds context about CDR standard conformance and product scoping, but it does not disclose response shape, pagination, or error behavior. With annotations in place, this is adequate but not rich.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two tight sentences with the core verb-resource pair front-loaded and a useful prerequisite in the second sentence. No filler, repetition, or irrelevant detail.

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?

Combined with the fully described schema and read-only annotations, the call pattern is complete: required parameters, optional filters, and prerequisite lookup are all covered. The main gap is the absence of an output schema and no explicit statement of the return shape, though referencing BankingProductLendingRateV2 partially compensates.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all five parameters, including enums and defaults. The description adds some clarifying context for productId and dataHolderBrandId, but it offers no additional meaning for loanPurpose, repaymentType, or lendingRateType beyond what the schema provides.

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 uses a specific verb 'Returns' and names the resource precisely: 'lending rates of a specific banking product (identified by Product ID) offered by a Data Holder'. This clearly distinguishes it from sibling rate tools like get_product_deposit_rates, and the CDR standard reference reinforces the tool's exact purpose.

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?

It explicitly instructs the agent to call GetDataHoldersByCategory first to obtain a valid Data Holder Brand ID, which is strong sequencing guidance. However, it does not explicitly state when not to use this tool or name alternative sibling tools, so it stops short of a 5.

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

A3.5/5.0
Disambiguation3/5

Tools are generally distinct in purpose (data holders, categories, constraints, etc.), but significant overlap exists between singular and plural variants (e.g., get_product_constraints vs get_products_constraints) and between generic and filtered variants (get_product_constraints vs get_product_constraints_by_type). Although descriptions clarify the differences, the names are too similar, leading to potential misselection.

Naming Consistency3/5

The naming follows a consistent 'get_<resource>_<detail>' pattern with snake_case. However, there is an inconsistency between singular ('product') and plural ('products') prefixes, and the inclusion of 'hello' breaks the pattern entirely. Overall, the pattern is recognizable but not uniform.

Tool Count3/5

With 17 tools, the count is on the higher side for a specialized data server. Several tools are essentially duplicates (singular vs. plural) that could be merged with a parameter. The 'hello' tool adds no value. The number of tools feels slightly bloated for the apparent domain, but not excessively so.

Completeness2/5

The tool set focuses on retrieving specific attributes (constraints, fees, features) for known product IDs, but lacks any tool to list or search for products. Without get_products or similar, an agent cannot discover product IDs needed to use the other tools, creating a critical workflow gap. Minor operations like product creation or update are not expected, but basic product listing is missing.

Resources