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Вопрос в избранное

save_favorite_question

Сохраняет вопрос в библиотеку аккаунта, а с указанным favorite_question_id — перезаписывает уже сохранённый. В библиотеке лежит снимок: правка исходного опроса библиотеку не меняет, и наоборот. До 100 вопросов на воркспейс.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYesСнимок вопроса — объект виджета из quiz://{id}/structure. До 64 КБ.
nameYesНазвание в библиотеке, до 255 символов.
choice_typeNoДля вопросов выбора: text или image.
widget_typeYesТип вопроса, как в структуре опроса (choice, input, matrix и т.д.).
workspace_idYesID воркспейса (из workspace://list).
source_quiz_idNoОпрос, из которого взят вопрос. Необязательно, только для справки.
choice_multipleNoДля вопросов выбора: разрешено несколько ответов.
source_widget_idNoUUID вопроса в этом опросе. Необязательно, только для справки.
favorite_question_idNoID сохранённого вопроса для перезаписи. Не передавайте, чтобы добавить новый.

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?

Beyond the annotations (write, non-idempotent, non-open-world) it discloses three non-obvious traits: the library stores a snapshot decoupled from the source quiz (edits don't propagate either way), the overwrite behavior of the favorite_question_id path, and a 100-question-per-workspace quota. It stops short of permissions/auth requirements or error behavior.

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?

Three short sentences, front-loaded with the primary action and its overwrite variant, then the snapshot caveat and the quota. No filler, though the snapshot sentence could be trimmed slightly.

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?

For a 9-parameter mutation with a nested data object and no output schema, the description covers the critical decision (add vs overwrite), the snapshot semantics, and the quota. Missing only peripheral items such as permission requirements and failure modes.

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 nine parameters including favorite_question_id, data, and the source_* reference fields. The description reinforces the favorite_question_id overwrite semantics but adds no syntax or format detail beyond the schema, so a baseline 3 is appropriate.

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 names a concrete verb+resource (saves a question into the account library) and clarifies the two modes of operation: new save vs. overwrite when favorite_question_id is supplied. Siblings like get_favorite_questions and delete_favorite_question are easy to tell apart by name, so the description is clear without needing to name them explicitly.

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

Usage Guidelines4/5

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

It gives the decisive usage fork: omit favorite_question_id to add, pass it to overwrite an existing saved entry. There are no explicit exclusions or named alternatives, but the context for choosing each mode is unambiguous.

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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