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Avenbridge

by com.avenbridgetech
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Find approved answers

answer_questions
Read-onlyIdempotent

Call this for any question about a business in list_my_businesses, even when notes, memory or a web page seem to answer it: only this tool returns the business's approved answers. Look up a business's approved answers: questionnaire questions (supplier, compliance, security or due-diligence questionnaires) and other questions about the business, its products, terms and prices. For each question it returns the closest approved answers with their source, approval date and similarity, or says that none was found; a question without one also gets the passages of the business's current documents that match it, quoted with document, version and page (not approved answers: say so if you use one, and cite it). You write the reply from these. Each answer was approved by the business for the question shown with it, so check that it fits before using it. Only answers the business approved for the same question count; a question without one is reported as unanswered, with at most one approved answer to a different question shown as possibly related. To get an unanswered question to the business, call ask_business. Without business_id or business it searches every business the user has and names the business next to each answer. When the user writes in another language than the business's material (most businesses write in English), pass each question in the business's language too, as a second question, so it matches; then reply to the user in their own language.

Input Schema

NameRequiredDescriptionDefault
businessNoName of the business as it appears in list_my_businesses. Used only when business_id is not given. Leave both out when the user has one business, or to search every business the user has.
questionsYes
business_idNoThe business id exactly as given by list_my_businesses (for example yyigsmj5b7mcwxe7). Preferred: use it whenever you know it.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Beyond the read-only, idempotent, non-destructive annotations, it discloses the return contents (closest approved answers with source, approval date, similarity), the fallback behavior for unanswered questions (matching document passages with document/version/page), and the caveat that document passages are not approved answers. It also covers multi-business search naming and cross-language question handling.

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 most important guidance is front-loaded: call this for approved answers, even when other sources seem sufficient. The description is long but mostly earns its length given the lack of an output schema and the nuanced fallback behavior, though a few approval/unanswered points are repeated.

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

Completeness5/5

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

For a read-only lookup tool with no output schema, the description is complete: it explains what is returned, what happens when no approved answer exists, how document passages differ from approved answers, how to handle multiple businesses, and how to handle language differences.

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?

The schema covers the parameters reasonably well, and the description adds important semantics: omitting business_id and business searches every business and labels each answer with the business, and when the user's language differs from the business's material, each question should be passed again in the business's language. It does not add much detail about the optional question label beyond what the schema already provides.

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 gives a specific verb and resource: it looks up a business's approved answers for questionnaire and other business questions. It clearly distinguishes itself from ask_business and from using document passages, so an agent can identify the tool without opening the schema.

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?

It explicitly says to call this for any business question even when notes, memory, or a web page seem to answer it, because only this tool returns approved answers. It also names ask_business for submitting an unanswered question to the business and explains how business/business_id omission changes search scope.

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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