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Local Pros by Ron Ventures

request_quote

Destructive

Send a quote request to one of the businesses returned by find_local_pros. The business gets an email with the customer's name, contact and problem and replies directly. Ask the user for permission before calling this: it shares their name and contact with the business.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesThe business slug from find_local_pros.
contactYesThe customer's phone number or email for the business to reply to.
problemYesWhat needs doing, where (city/neighborhood) and when.
customer_nameYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare destructiveHint=true, openWorldHint=true, so the external side-effect profile is known. The description goes further by explaining the mechanism (email to business) and the privacy consequence (shares the user's name and contact), justifying the destructive flag and the consent requirement. It stops short of describing what the caller gets back, keeping it at 4.

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?

Three tight sentences: purpose/mechanism first, deliverable second, consent requirement last. No redundancy or filler.

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?

With no output schema, the description clarifies the response path (the business replies directly by email), which is the key thing an agent needs. The only minor gap is not stating what the tool itself returns synchronously.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 75%, with customer_name undocumented in the schema; the description compensates by naming 'the customer's name, contact and problem' as the payload. It doesn't add format or syntax detail beyond the schema for slug/contact/problem, 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.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (send) and resource (quote request), and explicitly scopes it to 'one of the businesses returned by find_local_pros', tying it to the only sibling tool. An agent immediately knows what this does and where the required slug comes from.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives an explicit sequencing rule ('businesses returned by find_local_pros') and a hard precondition ('Ask the user for permission before calling this'). These are actionable when-to-use constraints, not implied guidance.

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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