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B2b Angies List

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.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityYesCity name, e.g. austin or 'san antonio'
stateYesTwo-letter US state code, e.g. tx
serviceYesAngi service slug, e.g. plumbing, electrical, roofing, house-cleaning, hvac

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true. Beyond that, the description adds critical decision-relevant behavior: source page type (angi.com companylist via residential proxy) and per-call pricing ($0.002 USDC, x402 on Base/Solana/Arc, failed calls not charged). This cost/success-billing detail is genuinely useful and not in annotations.

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?

Front-loads the resource and scope, then lists returned fields and closes with source and pricing. The field enumeration is dense but each clause maps to real outputs; not bloated for a data-heavy scraper, though the long field list could be trimmed given the output schema exists.

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?

For a read-only, open-world scraper with an output schema and annotations, the description is complete: it covers source, scope, cost, and content. The output schema already handles return-value detail, so the heavy field listing is somewhat redundant, but nothing an agent needs is missing.

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% and the schema already documents city/state/service with examples. The description reinforces the domain ('US city', service slug) but adds no syntax or format detail beyond the schema. Baseline 3 is appropriate.

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?

States a specific verb+resource: 'Angi (Angie's List) top-rated pros for a service in a US city'. This clearly distinguishes it from generic directory siblings like b2b_yellowpages, b2b_manta, and b2b_bbb by naming the Angi source and the specific scoping (service + US city).

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 context ('top-rated pros for a service in a US city') implies when to use it, but there's no explicit when-not or comparison against alternative contractor-directory siblings such as b2b_clutch_reviews, b2b_goodfirms_companies, or b2b_yellowpages. Usage must be inferred.

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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