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AdvocateMCP

by com.advocatemcp

Query Business Agent

query_business_agent

Ask a registered business's AI advocate a question and get a citation-ready answer plus a referral link. The answer is grounded ONLY in the business's public profile. Use this when a user asks something specific about one business (services, hours, policies, fit).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesBusiness slug identifier
queryYesThe visitor's question about this business
stageNoOptional buyer stage: browsing | comparing | committing
agent_idNoOptional self-asserted calling-agent id — used for logging/tuning only, never auth

TDQS

A4.2/5.0
Behavior4/5

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

The description discloses a key behavioral constraint not captured in annotations: 'The answer is grounded ONLY in the business's public profile.' It also describes the response format (citation-ready answer plus referral link), adding value beyond the annotations provided.

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?

The description is two sentences with the core action and output front-loaded, followed by a focused usage guideline. Every sentence adds value—no fluff or repetition.

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 tool with 4 parameters and no output schema, the description covers purpose, usage, output format ('citation-ready answer plus a referral link'), and a key constraint (grounding). It lacks explicit exclusions or preconditions, but is sufficiently complete for this scope.

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% with each parameter already described (slug, query, stage, agent_id). The description doesn't add parameter-specific details, but the baseline of 3 applies because the schema does the heavy lifting.

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 uses a specific verb 'Ask' with a clear resource ('registered business's AI advocate') and states the output ('citation-ready answer plus a referral link'). It distinguishes itself from sibling tools like get_availability or get_quote, which target narrower actions.

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

Usage Guidelines4/5

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

The description provides explicit context: 'Use this when a user asks something specific about one business (services, hours, policies, fit).' It doesn't explicitly name alternatives or say when not to use, but the usage scenario is clear and implies sibling tools cover other scenarios.

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

A4.3/5.0
Disambiguation5/5

Each tool targets a distinct action or resource: searching, quoting, reserving, confirming, payment handoff, callback, subscription, and business queries. Even related tools like reserve_slot and confirm_booking have clearly separated roles (holding vs. claiming). No overlapping purposes or ambiguous boundaries.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern in snake_case (e.g., search_businesses, get_quote, reserve_slot, confirm_booking). The verbs are varied but each is intuitive and fits the action. There are no mixed naming conventions or vague verb choices.

Tool Count5/5

13 tools cover the core booking and business-intelligence workflow without redundancy. The scope is well-defined—discovery, pricing, reservation, confirmation, payment, handoff, and subscription—so each tool earns its place. Not too thin, not overloaded.

Completeness3/5

The surface covers search, pricing, reservation, confirmation, payment, and handoff, but missing explicit cancellation or modification tools for bookings. A user asking to cancel a reservation would have no direct tool; get_cancellation_policy only provides text. Also no way to list a customer's existing bookings. This leaves notable gaps for a booking-focused server.

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