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Make a QR code

make_qr
Read-onlyIdempotent

Any text or URL → a QR code PNG you can embed or download. Stateless URL form: https://ainetcafe.com/i/qr/

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesThe text or URL to encode.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds the stateless URL form and confirms the PNG output, providing useful behavioral context beyond the structured metadata. No contradictions.

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, information-dense sentence followed by a concrete URL example. Every word earns its place, with no redundancy or filler.

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?

For a simple single-parameter tool with full annotations and an output schema, the description is complete. It explains what the tool produces, how it can be used (embed/download), and provides an alternative stateless invocation method, making it sufficient for an agent to select and invoke correctly.

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?

The schema already fully describes the 'text' parameter as 'The text or URL to encode.' The description repeats this in 'Any text or URL' but adds no new parameter semantics. Since schema coverage is 100%, baseline 3 is appropriate.

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: converting any text or URL into a QR code PNG that can be embedded or downloaded. This is a specific verb+resource construction and naturally distinguishes it from sibling tools like make_badge or text_to_image.

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 usage context: the tool returns an embeddable/downloadable PNG, and offers a stateless URL form for direct HTTP access. It doesn't explicitly mention when to use this over alternatives, but the purpose is so distinct that the context effectively guides 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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TDQS

A4.4/5.0
Disambiguation5/5

Each tool produces a distinct output type—badge, chart, QR code, diagram, spritesheet, or AI-generated image—so there is no overlap. The polling utility check_job is clearly separate from the generation tools.

Naming Consistency3/5

Three tools share the 'make_' prefix (make_badge, make_chart, make_qr), but others use different verbs (render_diagram, split_spritesheet, text_to_image, check_job). The naming is understandable but not uniformly consistent.

Tool Count5/5

With seven tools, the server is well-scoped for an image generation service. Each tool covers a specific image type or utility, and none seems superfluous.

Completeness4/5

The set covers a broad range of image generation needs (badges, charts, QR codes, diagrams, sprite sheets, AI images) and includes a job-polling mechanism for async operations. Minor gaps include lack of image editing tools (resize, crop, format conversion) and check_job referencing tools not in this server.