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Get Reviews Summary

get_reviews_summary
Read-onlyIdempotent

Get aggregated customer review statistics and featured review excerpts. Use this when a customer asks about product quality, other customers' experiences, or social proof. Returns ratings, distribution, and highlighted reviews.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
product_handleNoProduct handle: 'the-legacy-print', 'the-cinematic-print', or 'the-address-sign'. Omit for store-wide stats.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
noteNo
errorNo
scopeNo
sourceNo
messageNo
availableNo
total_reviewsNo
average_ratingNo
review_platformNo
_response_budgetNo
featured_reviewsNo
verified_purchase_countNo

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint, covering safety and idempotency. The description adds useful return semantics ('Returns ratings, distribution, and highlighted reviews') and the notion of 'featured' excerpts, which go beyond the schema. No contradictions found.

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 concise sentences with no filler. The first sentence states the action, the second gives usage guidance, and the third lists return components. Every sentence contributes value and the structure is front-loaded.

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?

This tool has a single optional parameter, a rich output schema, and strong annotations. The description adds the practical use case and return summary, making it complete for selection and invocation. No further explanation of return values is needed given the output schema.

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 coverage is 100% and the parameter description is detailed ('Product handle: ... Omit for store-wide stats.') The tool description itself does not add parameter-related meaning, so the baseline of 3 is appropriate.

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 opens with a specific verb and resource: 'Get aggregated customer review statistics and featured review excerpts.' It clearly distinguishes this tool from siblings like search_products or compare_products by focusing on review aggregation and social proof.

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 provides explicit when-to-use context: 'Use this when a customer asks about product quality, other customers' experiences, or social proof.' However, it does not explicitly mention when not to use it or name alternative tools, stopping 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

A3.9/5.0
Disambiguation3/5

Most tools hdistinct purposes, but search_products/search_products_task and check_photo_compatibility/check_photo_compatibility_task are direct-versus-task duplications of the same functionality. The descriptions note that one is task-based, so agents can tell them apart, but the overlap could still cause miselection.

Naming Consistency5/5

All tools use a consistent snake_case verb_phnoun pattern (get_, search_, check_, compare_, start_); task variants follow the same naming convention with a clear `_task` suffix. The convention is predictable and uniform.

Tool Count4/5

11 tools is within a reasonable range for a store assistant, and the scope covers discovery, comparison, recommendations, shipping, policies, and configuration. The two direct/task variant pairs add slight redundancy, making it feel a bit heavier than needed.

Completeness4/5

The tool surface covers core storefront workflows: product discovery/details, comparisons, recommendations, reviews, shipping, policies, photo compatibility, and configuration links. Snissing cart, checkout, or order-status tools feels acceptable if the server is scoped as a pre-purchase assistant, though those would be natural complements.

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