Yelp Remote MCP Server

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

No annotations are provided, so the description carries the transparency burden. It clearly indicates a read-only fetch and lists the returned fields, but it does not mention authentication needs, rate limits, or error behavior. This is adequate but not deeply transparent.

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?

The description is well-structured: a brief fetch statement, a concise enumeration of returned fields, and practical use cases. The opening line is slightly redundant with the title, but overall every sentence contributes useful context.

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 compensates by listing expected return fields. Required and optional parameters are covered by the schema, and use cases give an agent enough context to invoke the tool appropriately. Minor gaps around errors and data freshness remain.

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% and both parameters are already documented with descriptions and an enum for domain. The description adds little semantic detail beyond what the schema provides, such as the notion of 'domain targeting' and the Yelp ID/alias examples.

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?

Description states a specific action ('Fetches a single Yelp business by Yelp ID or alias') and identifies the resource and returned data. It clearly distinguishes itself from the sibling review and search tools by emphasizing 'single business' details.

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?

The description provides concrete use cases: enriching leads, monitoring competitor ratings over time, and validating hours/amenities. It does not explicitly contrast with sibling tools, but the context makes it clear when this details endpoint is appropriate.

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?

With no annotations provided, the description carries the full disclosure burden. It thoroughly describes pagination mechanics, nextPageToken semantics, the conflict between query and rating filters, notRecommended limitations, response echo fields, and the contents of each review and the business totals. This is exceptionally transparent for an unannotated tool.

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?

The description is long but justifiably so for a 10-parameter tool with subtle pagination and filter interactions. It is front-loaded with a clear summary, then logically organized into pagination, response contents, and use cases. Every sentence contributes useful information without fluff.

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?

There is no output schema or annotations, so the description must explain both invocation and expected returns. It covers pagination fields, review contents, author profile fields, photos/videos/reactions, tags, owner replies, and rating/language totals. This is a complete and self-sufficient description for selecting and invoking the tool 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 coverage is 100%, so the baseline is 3. The description adds meaningful cross-parameter guidance beyond the schema: step start by num, resend nextPageToken while keeping filters unchanged, do not combine start with nextPageToken, and paginate until hasNextPage is false. It also clarifies default behavior for num with and without notRecommended, which adds value beyond the individual parameter descriptions.

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 opens with the specific resource 'Yelp Place Reviews' and a clear verb, then states it fetches the review feed of a single Yelp business by Yelp ID with sorting, filtering, and pagination. This clearly distinguishes it from siblings like place details and search results, even without naming them.

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?

The description gives concrete use cases: monitoring sentiment, mining complaints, tracking owner responses, and building rating-distribution or review-velocity datasets. It also explains when filters behave unexpectedly, such as Yelp ignoring the rating filter when a query is set. However, it does not explicitly state when not to use this tool compared to the sibling search or details tools.

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?

With no annotations provided, the description carries the burden and covers core behavior: keyword/location search, optional map-bounded radius, domain targeting, offset-based pagination, and a ranked list of businesses with specific fields. It does not mention rate limits or response envelope details, but the disclosed behavior is solid for a GET search tool.

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?

The description is concise, front-loaded with the operation, and uses every sentence for meaningful detail. The opening line is slightly redundant with the title, but the rest of the description is tightly written and well organized.

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?

Since there is no output schema, the description usefully enumerates returned fields and downstream usage. It also explains pagination and domain targeting. It is missing notes on authentication, rate limits, or explicit sibling routing, but it gives enough context to invoke the tool correctly and interpret results.

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 baseline is 3. The description adds minor framing around `l` as map-bounded radius and `start` as pagination offset, but the schema already documents these parameters. It does not significantly deepen parameter understanding beyond structured definitions.

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?

Description identifies a specific operation: Yelp business search by keyword and location. It clearly distinguishes itself from sibling tools (place details, reviews) and lists concrete result contents. The purpose is immediately understandable.

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?

The description explicitly says to use search results and then pass returned aliases to the Yelp Place endpoint for full details, and gives use cases like local-discovery UIs and market-share datasets. It does not explicitly mention when to use Reviews or state exclusions, but the intended placement in the workflow is clear.

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