The Mine Works

search_realtor

Search Realtor.com for-sale or sold listings by city or ZIP. Returns price, beds, baths, sqft, county, listing status, and the listing agent and brokerage office for every record. No MLS login.

Input Schema

TableJSON Schema

Name	Required	Description
`minBeds`	No	Minimum bedrooms
`location`	Yes	City or ZIP (e.g. "Austin, TX")
`maxItems`	No	Max properties (default 50)
`maxPrice`	No	Maximum price
`minPrice`	No	Minimum price
`soldMode`	No	Return sold listings instead of for-sale (default false)

TDQS

A4/5.0

Behavior4/5

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

With no annotations, the description carries behavioral burden well by listing returned fields and noting sold mode via soldMode parameter. However, it omits potential rate limits, data freshness, and geographic scope (US only).

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?

Two concise sentences front-load the core action and return data, with no wasted words.

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

Completeness4/5

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

Given no output schema, the description adequately lists return fields and key parameters. Missing details on pagination or error handling, but still sufficient for a straightforward search tool.

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%, so the description adds marginal value beyond schema. It restates 'city or ZIP' and 'for-sale or sold' but does not deepen understanding of minBeds, maxPrice, etc.

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 clearly states it searches Realtor.com for-sale or sold listings by city or ZIP, specifies returned fields (price, beds, baths, etc.), and distinguishes from siblings like search_zillow and search_redfin by targeting Realtor.com.

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 indicates usage via city/ZIP and mentions 'No MLS login' for ease, but does not explicitly advise when to choose this tool over siblings (e.g., search_zillow) or provide exclusion criteria.

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

A3.5/5.0

Disambiguation4/5

Most tools target unique data sources or specific actions (e.g., search_zillow vs. get_zillow_property_details are clearly sequential). A few LinkedIn-related tools (find_linkedin_candidates vs. search_linkedin_employees) have overlapping purposes but their descriptions clarify distinct use cases. Overall, confusion is minimal and descriptions resolve ambiguity.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern in snake_case, using verbs like search, get, find, scrape, analyze, lookup, resolve, and verify. The pattern is predictable across the entire set, making it easy for an agent to infer function from name.

Tool Count2/5

With 32 tools, the server exceeds the 'too many' threshold of 25+. While the broad scope of web data mining justifies some diversity, the count is unwieldy and could overwhelm an agent's selection process. A smaller, more focused set per domain would improve coherence.

Completeness4/5

The toolset covers a wide range of data retrieval needs: company research, real estate, job listings, academic research, and government records. For a read-only data aggregation service, there are no major lifecycle gaps, though some subdomains like social media scraping only cover Reddit and LinkedIn, missing other platforms. Overall, it is reasonably complete for its stated purpose.

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