mcp-chat-cards

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Refine an efficient prompt

create_prompt_refine_card

Resolve gaps in a drafted prompt with concise multiple-choice questions, checkboxes for multi-select answers, and free-text options. Limits refinement to three rounds, then proceeds once the prompt is clear.

Instructions

Step 2 of the efficient-prompt flow: ask the fewest multiple-choice questions that close the gaps the gist left. Radios by default, checkboxes when several answers can be true at once; every question also gets a free-text "Other". At most 3 refine rounds - pass the round number so the card can say how many are left. Skip this step entirely when the gist is already clear enough to write the prompt.

Input Schema

TableJSON Schema

Name	Required	Description
`round`	No	Which refine round this is, 1 to 3 (default 1)
`title`	No
`subtitle`	No
`questions`	Yes
`contextActions`	No	Right-click menu actions the model anticipates being useful. Choosing one sends its prompt to the conversation; use {{selection}} to include the user's selected text.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`card`	Yes
`parts`	Yes	Split state, present on EVERY card result so one completeness check works for all card types. Cards that cannot split always report {current:1,total:1,hasMore:false}; create_markdown_card and create_code_tour_card pack oversized content into parts and can report more. Read hasMore rather than the card title to decide whether content was withheld.

Schema Changelog

Changes observed during successful MCP inspections.

Addedv0.2.0-alphaAug 29, 2026

TDQS

A4.2/5.0

Behavior4/5

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

With no annotations, the description carries the behavioral burden, and it handles it well: it discloses the multiple-choice format, radio/checkbox behavior, free-text 'Other', the 3-round limit, and the need to pass the round number. It omits details about return values or side effects, but the output schema exists and these are card-creation semantics.

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?

The description is three tight sentences with the core purpose first, followed by concrete behavioral details and the skip rule. There is no filler or redundancy.

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?

The description plus schema give enough for an agent to decide and call the tool: flow position, round bounds, skip condition, and question format. It references 'gist' without defining it, but that term is established by the sibling flow. Since an output schema exists, omitting return-value details is acceptable.

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 only 40%, so the description should compensate. It adds useful meaning to 'round' and implies the effect of 'multiple' through checkboxes, but it does not explain title, subtitle, questions structure, or contextActions, leaving those to the schema. The nested schema descriptions help, but the compensation is partial.

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 role: 'Step 2 of the efficient-prompt flow: ask the fewest multiple-choice questions that close the gaps the gist left.' This places it distinctly among siblings like create_prompt_gist_card and create_efficient_prompt_card. It is clear the tool produces a refine card, further confirmed by 'so the card can say how many are left.'

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 explicitly explains when to use it ('Step 2 of the efficient-prompt flow') and when not to ('Skip this step entirely when the gist is already clear enough'). It does not name alternative tools to use in the skip case, but the flow context makes the alternative implicit.

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