SiteCheck Company Records

Angi top-rated pros for a service in a US city: business

b2b_angies_list

Read-only

Angi (Angie's List) top-rated pros for a service in a US city: business name, rating, review count, recommend rate, sub-ratings (quality, value, punctuality...), years in business, city/state/ZIP, service area, emergency/free-estimate/warranty/veteran flags, payment methods, services offered, a top review and the Angi profile link, plus the city's overall rating for the service. From angi.com's public companylist pages via a residential proxy. Price: $0.002 in USDC per successful call, paid with x402 (Base, Solana or Arc); failed calls are not charged.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "service": "<service>",
      "city": "<city>",
      "state": "<state>"
    },
    "name": "b2b_angies_list"
  }
}

Input Schema

Name	Required	Description
`city`	Yes	City name, e.g. austin or 'san antonio'
`state`	Yes	Two-letter US state code, e.g. tx
`service`	Yes	Angi service slug, e.g. plumbing, electrical, roofing, house-cleaning, hvac

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 23, 2026

TDQS

A3.9/5.0

Behavior5/5

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

Annotations already establish readOnly and openWorld, and the description adds substantial context beyond that: it discloses the data source (angi.com public companylist pages via a residential proxy), the exact pricing model ($0.002 USDC per successful call via x402 on Base, Solana, or Arc), and that failed calls are not charged. This is exactly the kind of behavioral and cost transparency an agent needs before invoking a paid external-data tool.

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 front-loads purpose and then packs return fields, source, and pricing into two dense sentences. Every element is useful, but the long comma-separated field list is somewhat run-on and could be easier to scan if structured differently.

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 a simple three-parameter read-only lookup with a full output schema and existing safety annotations, the description covers the important missing pieces: data provenance and per-call pricing. It does not mention pagination, result limits, or response ordering, but those gaps are minor for this tool type.

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?

All three parameters have 100% schema description coverage with examples (city, two-letter state, Angi service slug), so the schema already carries the semantic load. The description does not add syntax or validation details beyond the schema, which is the expected baseline when schema coverage is high.

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 names the resource: Angi top-rated pros for a service in a US city, and enumerates the returned fields. It is specific enough that an agent can tell it retrieves business-directory data from Angi, but it never distinguishes itself from sibling directory tools such as b2b_yellowpages or b2b_manta.

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?

Usage is implied by the phrase 'top-rated pros for a service in a US city', which tells the agent the required inputs and likely use case. However, it gives no explicit when-to-use guidance, no alternatives, and no exclusions — an agent must infer that this is the right tool when Angi-specific reviews and sub-ratings are needed.

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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