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Get survey results

get_results
Read-only

What the survey found: the headline score and its breakdown, the written conclusion, and the topics people raised ranked by how many mentioned them, each with positive/negative counts and a few quotes.

Input Schema

NameRequiredDescriptionDefault
periodNoWhich responses to include. One of: all_time, last_month, current_month, current_year, last_year, or an exact range of days as YYYY-MM-DD..YYYY-MM-DD (both ends inclusive).all_time
survey_idYesID of the survey, as returned by list_surveys or create_survey.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / properties / period / description
      Added value: +"Which responses to include. One of: all_time, last_month, current_month, current_year, last_year, or an exact range of days as YYYY-MM-DD..YYYY-MM-DD (both ends inclusive)."
    • addedInput schema / properties / survey_id / description
      Added value: +"ID of the survey, as returned by list_surveys or create_survey."
  2. First observed

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds the return shape (score, breakdown, conclusion, ranked themes with sentiment counts and quotes), which is genuinely useful given there's no output schema, but it says nothing about pagination, result size, or how the period parameter affects aggregation.

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?

A single front-loaded sentence that leads with what the tool delivers, then enumerates components cleanly. No filler, though the trailing clause about quotes is somewhat long.

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 carries the burden of explaining return values and does so thoroughly, listing each component. The main gap is any mention of how time filtering changes the aggregation, but for a read-only results tool this is close to complete.

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%, with both parameters fully documented including the period enum-like values and range syntax, so baseline is 3. The description adds no supplementary meaning about survey_id or period behavior, but none is needed.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

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

The description clearly conveys the resource (survey results) and enumerates exactly what comes back: headline score, breakdown, written conclusion, ranked topics with counts and quotes. It never uses an explicit verb like 'retrieve' and doesn't distinguish itself from sibling get_survey, but the content is specific enough that an agent knows precisely what this tool yields.

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

Usage Guidelines2/5

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

There is no statement of when to call this versus get_survey, get_topic_quotes, or read_transcript, all of which overlap with survey/topic data. The description lists outputs but gives no selection criteria or prerequisites, leaving the agent to infer routing from tool names alone.

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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