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Glama

qr_generate

Generate QR code as SVG (base64 data URI included).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes
borderNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

B3.1/5.0
Behavior2/5

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

No annotations provided, so description must fully disclose behavior. It only mentions output format but omits details like error correction level, size, supported character sets, or whether the tool is read-only. For a generation tool, users need to know if it's safe and what constraints apply.

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

Conciseness4/5

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

Description is extremely concise (9 words) and front-loads the core action. However, the brevity sacrifices necessary detail about parameters and behavior, so it is efficient but not optimally informative.

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?

For a simple 2-parameter tool, the description minimally conveys the output format (SVG with base64 URI) but misses key details like the border parameter purpose and any limitations on input length or character encoding. It is adequate for basic usage but incomplete for thorough understanding.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description provides no additional meaning for the two parameters (text and border). It fails to explain that 'border' controls the quiet zone width or that 'text' is the content to encode. The description adds no value beyond the schema.

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?

Description clearly states 'Generate QR code as SVG (base64 data URI included)' which specifies the action (generate), output format (SVG with base64 data URI), and distinguishes from sibling tools (none of which produce QR codes).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use or avoid this tool, but the purpose is self-evident for QR code generation. No alternative tools exist among siblings, so differentiation is not needed. However, some context on typical use cases would improve score.

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

B3/5.0
Disambiguation5/5

Every tool has a clear, distinct purpose with thorough descriptions. Even closely related tools like base64_decode/encode and hash_md5/sha256 are easily differentiated by name and description.

Naming Consistency5/5

All tools follow a consistent lowercase_underscore naming convention, typically in a <domain>_<action> or <action>_<domain> pattern. There are no jarring deviations or mixed styles.

Tool Count1/5

193 tools is an extreme count, far beyond what any focused server needs. While each tool has utility, the sheer number creates a kitchen-sink effect that overwhelms agents and hinders discoverability.

Completeness4/5

Within each subdomain (JSON, cron, JWT, etc.), the coverage is exhaustive, covering validation, conversion, parsing, and more. Minor gaps exist (e.g., YAML-to-TOML conversion missing), but overall it is remarkably complete.