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LouisChanCLY

napkin-ai-mcp

by LouisChanCLY

Generate Visual and Save

generate_and_save

Generate a visual from text content and save it to your configured storage. Supports SVG, PNG, and PPT formats with options for style, orientation, and multiple variations.

Instructions

Generate a visual, wait for completion, and save to configured storage. Requires storage to be configured in server settings.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
widthNoWidth in pixels (PNG only)
formatNoOutput format: svg, png, or ppt (default: svg)
heightNoHeight in pixels (PNG only)
contentYesMain text content to visualise
contextNoAdditional context for visual generation
dry_runNoValidate inputs without calling the API (default: false)
filenameNoCustom filename (without extension). Auto-generated if not provided.
languageNoBCP 47 language tag (e.g., en, en-GB). Default: en
style_idNoStyle identifier from Napkin AI
visual_idNoRegenerate a specific visual layout with new content. Cannot be used with visual_ids, visual_query, or visual_queries.
color_modeNoColour mode: light, dark, or both
visual_idsNoArray of visual IDs to regenerate specific layouts. Length must match number_of_visuals.
orientationNoOrientation: auto, horizontal, vertical, or square
visual_queryNoVisual type query (e.g., mindmap, flowchart, timeline)
sort_strategyNoSort strategy: relevance, random, or variation
visual_queriesNoArray of visual type queries. Length must match number_of_visuals.
number_of_visualsNoNumber of variations to generate (1-4)
text_extraction_modeNoText extraction: auto, rewrite, or preserve
transparent_backgroundNoUse transparent background

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
filesYesSaved files with storage locations
creditsNoCredit consumption for the request
request_idYes
Behavior3/5

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

With no annotations provided, the description must fully disclose behavioral traits. It honestly states the side effect of saving and the asynchronous waiting behavior. Yet it omits details such as failure handling, return value semantics, or storage specifics, leaving some informational gaps beyond what the schema provides.

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 a single, front-loaded sentence that efficiently states the core workflow. Every word earns its place, with no filler or repetition of schema content.

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

Completeness3/5

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

Given the tool's complexity (19 parameters) and the rich schema and output schema, the description provides a minimal but adequate high-level overview. It covers the key workflow (generate, wait, save) but lacks contextual details about multi-visual generation, regeneration, or failure modes. These gaps are partially mitigated by the schema's parameter descriptions, making the description adequate but not comprehensive.

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 description adds no parameter-level meaning, but since the schema already documents all 19 parameters with descriptions and constraints, no extra compensation is needed.

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 clearly states the tool's function: 'Generate a visual, wait for completion, and save to configured storage.' This distinguishes it from siblings like generate_visual and generate_and_wait, which focused on generation without saving. The verb+resource structure is specific and unambiguous.

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 description provides clear context: it generates, waits, and saves, and explicitly notes a prerequisite ('Requires storage to be configured in server settings'). However, it does not explicitly contrast with generate_and_wait or other alternatives, so I deduct one point for lacking explicit when-to-use vs. alternative guidance.

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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