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question_update

Edit a pending question's text or set its state to defaulted or withdrawn. Revalidates changes; answered or withdrawn questions stay locked.

Instructions

Edit a pending question's text (question, header, options, default_answer; the whole result is revalidated) or move it out of pending with state=defaulted (you acted on your default) or state=withdrawn (moot). A defaulted question can still be withdrawn. Moving state needs the asking session or the human; an answered or withdrawn question cannot be changed. The ref, asker and wake target never change.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
stateNo
headerNo
optionsNo
questionNo
question_idYes
default_answerNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
stateYes
hive_noticeNo
question_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.11.5

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already cover read-only, destructive, idempotent, and open-world hints. The description adds substantial behavioral context beyond those: revalidation after edits, the state machine (defaulted can still be withdrawn), permission requirements for state changes, and immutable fields (ref, asker, wake target).

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 description is dense but front-loaded with the core action before moving into state semantics and constraints. Every sentence carries useful information, though the single long paragraph could be slightly more scannable.

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?

Given the mutation tool's complexity, the available annotations, the input schema, and the presence of an output schema, the description supplies the missing state-machine rules, permissions, and immutability constraints. An agent has enough to invoke it correctly without needing return-value details in the description.

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?

With 0% top-level schema description coverage, the description compensates by naming the editable text fields (question, header, options, default_answer) and explaining the state parameter's two enum values and their meanings. It does not explicitly describe question_id, but the purpose sentence and required-field context make its role inferable.

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 states a specific verb and resource: edit a pending question's text or move it out of pending via state. It clearly distinguishes update from other question operations like ask/get/list/answer by focusing on pending-question modification and state transitions.

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 explicit when-to-use conditions (editing pending text, setting state=defaulted or withdrawn) and when-not constraints (answered or withdrawn questions cannot be changed; moving state needs the asking session or human). It does not name alternative sibling tools, so it falls short of a full 5 but provides strong contextual routing.

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