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RateSonar MCP

find_products

Read-onlyIdempotent

Find current products by lender and words in the product name, e.g. institution "CBA" and query "standard variable". Returns institution_id and product_id for each match, with category, rate and observed_date. A product is the pair (institution_id, product_id): pass both to rate_history or rate_details. Use compare_rates instead to rank lenders for a category.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoProducts to return. Default 10.
queryNoWords in the product name, e.g. "standard variable" or "bonus saver".
categoryNoOptional product category.
institutionNoA lender id or name, e.g. "cba", "Westpac", "Bendigo Bank".

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive and non-open-world, so the safety profile is covered. The description adds real behavioral context: results are limited to *current* products, and each match carries category, rate and observed_date. It does not discuss pagination or matching/fuzzy-search behavior, keeping it short of a 5.

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?

Three tight sentences, front-loaded with the verb+resource and an example, followed by return fields and routing. No sentence is wasted.

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?

With no output schema, the description compensates by naming the returned fields (institution_id, product_id, category, rate, observed_date) and the key identity semantics of a product pair, while annotations carry the safety profile. An agent has everything needed to call and chain it.

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 parameters (limit, query, category, institution) are already fully documented, and the description's examples for institution and query duplicate the schema's. It adds little input-side meaning beyond the schema, so the baseline 3 applies.

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?

States a specific verb and resource with scope: 'Find current products by lender and words in the product name,' plus a concrete example ('CBA' / 'standard variable'). It also defines what a product is, which disambiguates it from the sibling tools that operate on series and rates.

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 routes to an alternative ('Use compare_rates instead to rank lenders for a category') and tells the agent what to do with the result ('pass both to rate_history or rate_details'). The condition that selects this tool versus its siblings is stated rather than inferred.

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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