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HasData

hasdata-mcp

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google_maps_reviews: GET /

hasdata_google_maps_reviews_getMapReviews

Retrieve paginated Google Maps reviews for a place using dataId or placeId, with sorting, topic filtering, and language selection. Supports reputation management, sentiment analysis, and competitor benchmarking.

Instructions

Get Map Reviews

Paginated fetch of Google Maps reviews for a place by dataId or placeId, with sort (qualityScore, newestFirst, ratingHigh, ratingLow), topicId filter, and language. Returns per-review author name and profile link, star rating, text, published/relative date, likes count, owner response, attached photos, and local-guide flag. Use for reputation management, sentiment and topic mining, competitor review benchmarking, and feeding review data into summarization or trust-score LLMs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataIdNoGoogle Maps data ID.
placeIdNoUnique reference to a place on a Google Map. Either dataId or placeId should be set.
hlNoThe two-letter language code for the language you want to use for the search.
sortByNoParameter used for sorting and refining results.
topicIdNoDefines the ID of the topic you want to use for filtering reviews.
nextPageTokenNoDefines the next page token. It is used for retrieving the next page results.
Behavior2/5

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

No annotations are provided, so the description fully bears the responsibility. It describes the tool as a paginated fetch and lists return fields, but omits how pagination works (e.g., nextPageToken usage), rate limits, or authentication. This leaves key behavioral details unclear.

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 a single paragraph that front-loads the purpose and efficiently conveys key information. It could be better structured (e.g., bullet points for return fields), but it is clear and without excessive verbosity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the main purpose, parameters, and return data, which is sufficient for a simple read tool. However, it lacks explanation of pagination mechanics (how to use nextPageToken) and error conditions, leaving some gaps given no 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?

The input schema has 100% parameter description coverage, providing basic definitions. The description adds value by explaining sorting options (qualityScore, newestFirst, etc.) and the topic filter, but does not elaborate on parameters beyond what schema already states.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool fetches Google Maps reviews for a place, using dataId or placeId, with sorting, filtering, and language options. It distinguishes itself from sibling tools like 'getMapPhotos' by focusing on reviews, but does not explicitly differentiate from the contributor reviews tool.

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

Usage Guidelines3/5

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

The description lists specific use cases (reputation management, sentiment mining, etc.), providing clear context for when to use the tool. However, it does not mention when not to use it or compare with alternative tools (e.g., contributor reviews).

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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