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LouisChanCLY

napkin-ai-mcp

by LouisChanCLY

Verify API Key

verify_api_key

Check if your Napkin AI API key is valid to ensure your setup works before creating visuals.

Instructions

Verify that the configured Napkin AI API key is valid. Use this to test your setup before generating visuals.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNoError message if invalid
validYesWhether the API key is valid
base_urlYesAPI base URL being used
Behavior3/5

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

With no annotations, the description carries the burden of behavioral disclosure. It states the tool verifies validity, implying a read-only check, but does not explain what happens on failure, whether it makes a network request, or what the response contains. The existing output schema may cover return format, but the description lacks richer behavioral context.

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 two sentences, directly states the purpose and usage, and contains no filler or redundant information. It is well-structured and easy to parse quickly.

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?

Given the tool's simplicity (0 parameters, output schema present, low complexity), the description is nearly complete. It conveys the purpose and when to use it. The only minor gap is the lack of detail on failure behavior, but this does not significantly impact usability for a simple API key check.

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?

The tool has zero parameters, so the baseline is 4. The description adds value by indicating the tool tests the configured API key, which gives context for why there are no user-supplied inputs. No additional parameter semantics are 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 identifies the action ('Verify') and the resource ('configured Napkin AI API key'), with a specific objective ('is valid'). It is distinct from sibling tools like generate_visual or download_visual, which perform different operations.

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 phrase 'Use this to test your setup before generating visuals' provides explicit context for when to use the tool. It does not mention alternatives or exclusions, but for a simple validation tool with zero parameters, this guidance is sufficiently clear.

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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