Yellow Pages Remote MCP Server

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

Annotations already declare readOnlyHint=true, openWorldHint=true, destructiveHint=false, covering the safety/live-data profile. The description adds one genuinely useful behavioral trait: unpublished fields are omitted from the response. However, it says nothing about scraping latency, rate limits, or failure modes for a live scraper, so it adds only modest context beyond 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?

Front-loads purpose, then the field list, then caveats, then use cases in a logical order. The long enumeration of returnable fields is dense but earns its place given there is no output schema. Minor verbosity in the field list.

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?

Given a single-param, no-output-schema scraper with annotations covering safety, the description is nearly complete: it lists returned fields, notes field omission, and gives use cases. It lacks only operational caveats (latency, throttling, bad-URL behavior) that would matter for a live scraper.

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% for the single url parameter, so the schema already documents it and baseline 3 applies. The description restates the URL source (yellowpages.com listings) but adds no format, canonicalization, or validation guidance beyond the schema.

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 (scrapes/returns) and resource (a single YellowPages business listing URL), and enumerates the returned business data fields. Sibling search_getSearchResults is implicitly distinguished by 'a single ... URL' vs. the search endpoint referenced in the usage sentence.

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?

Explicitly names three use cases (hydrate a lead with verified NAP data, build a B2B contact database, validate business legitimacy) and routes the agent to the sibling Search endpoint as the source of URLs. Clear when-to-use with an alternative input source.

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 cover the safety profile (readOnly, non-destructive, open-world), so the bar is lower; the description still adds real behavioral detail such as the sort parameter being valid on yellowpages.com only and page-based pagination. It does not discuss rate limits or result caps, 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.

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

The description is front-loaded with the core operation before moving to return fields and use cases, and every sentence carries information. The final sentence is dense with two distinct use cases but not padded.

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 usefully enumerates returned fields (name, listing URL, phone, address, categories, rating, review count, years in business), which is exactly what an agent needs to judge fit. It omits pagination termination behavior and how many results per page, a minor remaining gap for a search tool.

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 and the schema carries most parameter meaning. The description adds one genuinely new constraint not in the schema: the sort enum is restricted to yellowpages.com. It does not explain pagination semantics or default page behavior, so it is above baseline but not rich.

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 ('Runs a YellowPages business search by keyword plus location') and enumerates the dimensions it controls (sort, domain, pagination). It also differentiates itself from the sibling by naming the YellowPages Place endpoint as the downstream enrichment step rather than a competing search path.

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 clear positive usage contexts (B2B lead generation by niche and city, geo-targeted prospect lists) and explicitly names the sibling tool it feeds into. It stops short of stating when not to use it or any prerequisite conditions, so it lands at clear-context-without-exclusions.

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