Yelp Remote MCP Server

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

Annotations already declare readOnlyHint=true, openWorldHint=true, and destructiveHint=false, so the safety profile is covered. The description adds real context beyond that by enumerating what the response contains (name, address, price range, categories, hours, amenities, photos, highlighted reviews) and noting domain targeting, and it is consistent with the annotations.

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

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

Three sentences, front-loaded with the core action, then the return payload, then the use cases. The long return-value list earns its place because there is no output schema, though the opening title line 'Get Yelp Place Details' is a slight restatement of the name.

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

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

With read-only annotations, 100% schema coverage on two simple params, and no output schema, the description closes the remaining gaps by listing the returned fields and the scenarios that justify a call. An agent has everything needed to select and invoke it correctly.

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

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

Schema description coverage is 100%, so both placeId and domain are already documented in the schema. The description only restates that lookup is 'by Yelp ID or alias with domain targeting' and adds no format examples, validation rules, or default behavior beyond what the schema provides. Baseline 3 applies.

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

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

The description states a specific verb and resource: 'Fetches a single Yelp business by Yelp ID or alias.' The word 'single' and the reliance on Yelp ID/alias imply differentiation from the sibling search and reviews endpoints, though no sibling is named explicitly, which keeps this short of a 5.

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

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

It gives three concrete use cases: enriching leads/listings, monitoring a competitor's rating/review count, and validating hours/amenities before display. That is strong when-to-use guidance, but there is no explicit when-not-to-use or direct alternative (e.g. use yelp_search to find the ID first).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already establish read-only, non-destructive, open-world behavior. The description adds real value beyond that: the two mutually exclusive paging strategies, the requirement to keep filters constant across pages, the loop-until-hasNextPage stop condition, and the fact that notRecommended reviews omit photos/videos/reactions.

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

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

Purpose and pagination are front-loaded before the long return-value enumeration. The inventory of review fields is lengthy, but it earns its place since no output schema exists to document the payload.

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

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

With no output schema, the description fully covers the return shape (author profile, text, rating, photos, reactions, tags, owner reply, business rating/language totals) and the pagination contract. Combined with 100% schema coverage, an agent has everything needed to call and page correctly.

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

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 every parameter, including the start/num/nextPageToken interaction. The description's paging walkthrough (step start by num, or resend nextPageToken) synthesizes the schema but adds little that isn't already there, matching the baseline 3.

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

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

States a specific verb and resource ('Fetches the review feed of a single Yelp business by Yelp ID') with scope, and the Yelp branding plus 'single business by Yelp ID' clearly distinguishes it from the Amazon/Google Maps/Walmart review siblings.

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

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

Gives explicit pagination procedure and concrete use cases (sentiment monitoring, competitor complaint mining, response tracking, rating-distribution datasets). It does not name the sibling that supplies the placeId (yelp_search_getSearchResults) nor state when to prefer it over other review sources, so it stops short of 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare readOnlyHint/openWorldHint/destructiveHint, so the safety profile is covered. The description adds behavior beyond that: it enumerates the returned fields (alias/ID, name, categories, rating, review count, price tier, thumbnail) and notes pagination is offset-based, which matters since there is no output schema.

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

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

Purpose and scope are front-loaded in the first sentence, with the return shape and downstream uses following. The final clause stacks three use cases, which is slightly listy, but nothing is wasted or circular.

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

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

For a 5-parameter read-only search tool with no output schema, the description covers the required inputs, the optional radius/domain/pagination behavior, and the return contents. It is complete enough to invoke correctly; only auth/rate-limit context is absent, which is minor for this tool class.

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

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

Schema coverage is already 100%, so the baseline is 3, but the description genuinely clarifies the `l` parameter's meaning ("map-bounded radius ... g:lon1,lat1,lon2,lat2"), which the schema only demonstrates by bare example, and labels `start` as offset-based pagination. It adds real meaning over the structured fields.

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

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

The description names a specific verb and resource ("Runs a Yelp business search by keyword and location") and scopes it further with the optional map-bounded radius, domain targeting, and offset pagination. It also differentiates itself from the sibling place endpoint by saying returned aliases feed into it, so an agent can tell the search tool apart from the detail tool.

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

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

It gives concrete usage context: feed returned aliases to the Yelp Place endpoint for details, or use results for local-discovery UIs and competitor/market-share datasets. It stops short of explicit exclusions (e.g., when to prefer the reviews endpoint instead), but the when-to-use context is clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.