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Question breakdown

question_breakdown
Read-onlyIdempotent

Deep results for ONE question: response count, average (rating questions), the full option distribution (option label, count, %) for multiple-choice/rating/ranking, and top phrases for open-ended. For ranking questions the distribution counts FIRST-place ranks only (each respondent contributes one), so % is the share of respondents who ranked that option top. Resolve question ids via project_overview's questions list. Optional since/until window the results.

Input Schema

NameRequiredDescriptionDefault
sinceNoISO date lower bound, or null.
untilNoISO date upper bound, or null.
projectIdYesThe project the question belongs to.
questionIdYesThe question id (from project_overview.questions).
includeLowQualityNoLow-quality (archived) responses are excluded by default. Set true ONLY when the user explicitly asks to include low-quality/archived responses.

Output Schema

NameRequiredDescriptionDefault
errorNo
averageNo
keywordsNo
questionNo
distributionNo
responseCountNo

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 establish readOnly/idempotent/non-destructive, so the safety profile is covered. The description adds a genuinely non-obvious semantic beyond that: for ranking questions the distribution counts first-place ranks only and the percentage is the top-rank share of respondents, preventing misinterpretation of the output.

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-loaded with the core purpose, then the ranking caveat, then the id-resolution pointer. Dense but largely earning its place; the trailing fragment 'Optional since/until window the results' is awkward and adds little.

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 an output schema present, return values need not be explained, yet the description still conveys output shape; combined with annotations and full schema coverage, an agent has enough to invoke it correctly. The missed includeLowQuality flag and lack of alternative-tool routing are the only minor omissions.

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 description coverage is 100%, so the schema already documents all five parameters. The description only restates the since/until window ('Optional since/until window the results') and omits any mention of includeLowQuality, adding no meaning 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 resource and scope: 'Deep results for ONE question' and enumerates exactly what it returns (response count, average, option distribution, top phrases). The 'ONE question' scoping plainly distinguishes it from multi-question and channel-oriented siblings like channel_breakdown.

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?

It gives a concrete prerequisite for obtaining the required id ('Resolve question ids via project_overview's questions list'), which is useful. However, it never states when to prefer this over near-neighbors such as channel_breakdown, get_question, or response_detail, so selection guidance is only implied.

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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