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Публичная ссылка на ответы

share_answers_link

Создает публичную ссылку на ответы респондентов опроса.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoРежим выборки ответов: full=все ответы, in=только из answerIds, not_in=все кроме answerIds, answer=один конкретный ответ. По умолчанию full.
date_toNoКонец периода в формате Y-m-d (например 2024-12-31).
quiz_idYesID опроса.
timezoneNoЧасовой пояс для дат (например Europe/Moscow). По умолчанию — timezone пользователя.
answerIdsNoСписок ID конкретных ответов. Используется при type=in или type=not_in.
date_fromNoНачало периода в формате Y-m-d (например 2024-01-01).
is_deletedNoБрать удалённые ответы вместо активных (по умолчанию false).
is_completeNotrue = только завершённые ответы (по умолчанию true).
is_screenoutNoВключать ответы, дисквалифицированные логикой (по умолчанию false).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.9/5.0
Behavior2/5

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

Annotations already declare readOnlyHint=false, idempotentHint=false and openWorldHint=true, so the agent knows this is a non-idempotent write that affects an external surface. The description adds nothing beyond that: it does not say a new link is generated per call, whether old links are invalidated, what permissions are required, or that the link is publicly accessible without auth. With annotations covering the safety profile, the remaining burden is on the description, which stays silent.

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 with no filler; it is efficient. It is arguably under-specified rather than padded, so it does not lose points for verbosity.

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

Completeness2/5

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

For a 9-parameter tool that creates a shared public link with no output schema, the description omits essential context: whether the returned link is stable across calls, permission requirements, and how it relates to the other share_* tools. One sentence is insufficient for the tool's complexity.

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 all nine parameters (type enum, date filters, answerIds, is_deleted, is_complete, is_screenout, timezone) are already fully documented in the schema. The description adds no filtering or formatting semantics, so the baseline 3 for high schema coverage applies.

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 states a clear verb+resource in Russian: creating a public link to survey respondents' answers. It is distinguishable from report/summary siblings by naming 'ответы респондентов', but it never explicitly contrasts itself with share_report_link, share_summary_link or share_ai_report.

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 guidance on when to use this tool versus the sibling sharing tools (share_report_link, share_summary_link, share_ai_report), and no prerequisites or exclusion conditions are stated. The agent must infer usage purely from the tool name.

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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