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RealMarket Survey Builder

Server Details

Draft consumer market-research questionnaires for packaging, concepts, pricing and more.

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Status
Healthy
Last Tested
Transport
Streamable HTTP · MCP 2025-11-25
URL
ChatGPT
–
Claude
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TDQS

A4.4/5.0

Scored across 1 tool

Disambiguation5/5

There is only one tool, so there is no possibility of confusion or misselection. The tool's purpose is stated precisely (consumer questionnaire drafting) with explicit exclusions, leaving no boundary ambiguity.

Naming Consistency5/5

The single tool follows a clear verb_noun snake_case pattern (build_consumer_questionnaire). No mixed conventions or vague verbs are present, so the naming is fully predictable for any future additions.

Tool Count3/5

One tool for an entire 'Survey Builder' server is thin, even for a narrow drafting scope. The tool is rich and self-contained, but the surface offers no handles for adjacent steps (revising, listing templates, exporting), which the name implies.

Completeness3/5

Drafting is covered well, including screening, answer formats, and fieldwork notes, but there are notable gaps: no update/revise tool for iterating on a draft, no template or saved-questionnaire retrieval, and no export/format conversion. Agents can work around this by editing in conversation, but not by any tool call.

Available Tools

1 tool
build_consumer_questionnaireBuild a consumer questionnaireA
Read-onlyIdempotent
Inspect

Use when drafting a consumer questionnaire for packaging, concepts, pricing, repeat purchase, purchase frequency, non-buyers or brand perception. Returns up to 15 questions in complete blocks with screening, answer formats, purposes and fieldwork notes. English source; translate the complete draft in the conversation if requested. Pricing requires currency and product_unit. Missing images do not block drafting. Do not use for recruitment, response collection, messaging or unrelated requests. Operational tool calls are logged.

NameRequiredDescriptionDefault
productYesProduct or brand supplied by the user, e.g. Acme cereal. Preserve its name.
audienceYescategory_buyers: category purchase in past 3 months; brand_buyers: brand purchase in that period; competitor_buyers: other brands but not this brand in that period, possibly former brand buyers; never_buyers: recent category buyers who never bought the brand; previous_brand_buyers: any past brand purchase, even without recent category purchases. Repeat purchase excludes never_buyers; non_buyers excludes brand_buyers and previous_brand_buyers.
categoryYesConsumer product category, e.g. breakfast cereal. Ask if missing or ambiguous.
currencyNoRequired for pricing, including extra topics. User-supplied three-letter uppercase code, e.g. USD; no conversion.
objectiveYesMap the user's goal to one supported objective; brand_perception is a value, not a tool name.
extra_topicsNoOnly additional topics requested by the user. Same audience restrictions apply as for the primary objective; complete blocks may be omitted at 15 questions.
product_unitNoRequired for pricing, including extra topics. User-supplied unit, e.g. 500 g pack.
business_questionYesShort user-provided research decision or question. Recorded as context, not interpreted by the server.

Output Schema

NameRequiredDescription
goalYes
titleYes
sectionsYes
screeningYes
limitationsYes
omitted_topicsYes
question_countYes
fieldwork_notesYes
business_questionYes

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds genuinely new behavior: the 15-question cap with possible omission of complete blocks, English-only source with in-conversation translation, the pricing prerequisite on currency and product_unit, and that calls are logged. The only soft spot is 'Missing images do not block drafting', which references no parameter in the schema and reads as residue from another context.

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 definition is front-loaded with the use case, then output shape, then language, then prerequisites, then exclusions — a sensible ordering with almost no filler. A couple of clauses are compressed to the point of being cryptic ('Missing images do not block drafting'), which costs a little clarity without adding bulk.

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 an 8-parameter tool with 5 required fields, an output schema, and full annotation coverage, the description covers the remaining agent-facing questions: output volume, block structure, language handling, the pricing prerequisite, and the boundary against recruitment or messaging use. Nothing needed to invoke it correctly is missing.

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 100%, so the baseline is 3. The description still adds cross-parameter meaning the schema only states per-field: 'Pricing requires currency and product_unit' ties two optional parameters to one objective, and 'Same audience restrictions apply as for the primary objective' explains how extra_topics interacts with audience selection.

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 names the specific resource (a consumer questionnaire) and enumerates the exact scope it covers: packaging, concepts, pricing, repeat purchase, purchase frequency, non-buyers, brand perception. Combined with 'Returns up to 15 questions in complete blocks with screening, answer formats, purposes and fieldwork notes', an agent knows precisely what the tool produces 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?

Explicit when-to-use is given via the objective list, and explicit when-not-to-use follows: 'Do not use for recruitment, response collection, messaging or unrelated requests.' No sibling tools exist, so no alternative routing is needed; the exclusions do the routing work instead.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 1 tool update
    • First observedbuild_consumer_questionnaire

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