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Insert ranking question

editor_insertRankingQuestion

Insert a ranking question. Use when the respondent must order items by preference (drag to rank). Requires 2+ options as a native string array. Example: {title:"Rank these features", options:["Speed","Price","Design"]}.

Input Schema

NameRequiredDescriptionDefault
afterNoNodeId to insert after. Use $prev to chain. Omitting appends to end (usually wrong).
titleYesQuestion title
formIdYesForm ID to insert into
optionsYesItems to rank (minimum 2, non-empty, unique)
isHiddenNoStart hidden (the target of a `show` rule).
parentIdNoParent node ID to insert into (e.g., column1)
positionNoPosition among siblings: inside parentId when given, else at the top level ('first' = top of the form, e.g. a title). Not combinable with after.
requiredNoWhether question is required. Default: true. Pass false to make the field optional.
randomizeOptionsNoShuffle starting order per respondent

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / randomizeOptions
      Added value: +{
      +  "description": "Shuffle starting order per respondent",
      +  "type": "boolean"
      +}
  2. First observed

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=false and destructiveHint=false, so the mutation/safety profile is covered. The description adds the 2+ option requirement and format ('native string array'), but that largely restates the schema's minItems constraint and adds little about insertion side effects, positioning behavior, or defaults that isn't already in the schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short sentences, front-loaded with the action, then the selection cue, then the hard requirement and a concrete example. Every sentence earns its place with no padding.

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 an insert tool with no output schema and a fully documented 9-parameter schema, the description covers purpose, usage, and a valid example. It stops short of noting structural pitfalls the schema hints at (e.g., 'after' vs 'position' incompatibility), but nothing essential for calling it is missing.

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 baseline is 3. The worked example clarifies the title/options shape, but the description does not add meaning beyond what the schema already documents for the other seven parameters (after, position, parentId, etc.).

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 verb and resource ('Insert a ranking question') and immediately differentiates the question type from its many siblings by defining the respondent behavior ('order items by preference, drag to rank'). An agent can distinguish this from insertRatingQuestion or insertRadioQuestion without opening either schema.

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?

The clause 'Use when the respondent must order items by preference (drag to rank)' gives a clear selection context against sibling question types. It does not explicitly name alternatives or when-not conditions, but the semantic cue is strong enough for correct selection.

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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