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Glama

Brandize

by me.brandize

generate_logo_variations

Generate alternate style directions for an existing generate_logo job. Free — no checkout — but limited to this job's free-preview credit (1 by default; a COMPLETE purchase grants 2 more, other tiers grant none). Returns the same kind of watermarked, low-res preview as generate_logo, plus how many free credits remain. Before any purchase, each result's variationId can be passed to buy_logo_variation to purchase that design instead of the original. On an already-purchased COMPLETE job, this instead adds more alternates to the deliverable itself (retrieve via get_logo_result as usual) — call it again there if the user wants more once revisionCredits allows. Any other purchased tier refuses outright — its deliverable is fixed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNoHow many alternate-style variations to generate (1-3), capped by the free-preview credits remaining on this job.
jobTokenYesThe jobToken returned by generate_logo.

Schema Changelog

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

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden, and it does so thoroughly. It discloses that results are watermarked/low-res previews, that free credits are consumed and reported, that variationId can be used with buy_logo_variation, and how purchased COMPLETE jobs differ from other purchased tiers. This is far beyond minimal behavioral disclosure.

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 long but every sentence earns its place given the tool's genuinely branching behavior across credit states and purchase tiers. It front-loads the core purpose and then structures the credit, preview, purchase, and post-purchase cases in logical order with no 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?

There is no output schema, so the description correctly explains the return value: a watermarked low-res preview plus remaining credits, with variationId available for purchase. It also covers all relevant usage states and alternatives, leaving no critical gap for an agent deciding whether and how to invoke the tool.

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?

Schema description coverage is 100%, so the schema already documents count and jobToken. The description adds meaningful context by tying count to the free-preview credit cap ('capped by the free-preview credits remaining') and explaining how results relate to variationId, which helps an agent reason about the tool without opening 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?

The description opens with a specific verb and resource: 'Generate alternate style directions for an existing generate_logo job.' It clearly distinguishes this tool from generate_logo (which creates the original job) and buy_logo_variation (which purchases a variation), so an agent can tell what it is for.

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

Usage Guidelines5/5

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

The description gives explicit usage context: it applies to an existing generate_logo job, is free for preview, and behaves differently before purchase, after a COMPLETE purchase, and on other purchased tiers. It also points to buy_logo_variation for purchasing a generated variation and get_logo_result for retrieving deliverables, spelling out when-not conditions like 'Any other purchased tier refuses outright.'

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

A4.3/5.0
Disambiguation5/5

Each tool targets a distinct resource or action: logo generation, logo variations, variation purchase, result polling, color palette, meta tags, schema markup, pricing, blog search, and health check. The two logo-generation tools are clearly differentiated by new-job vs existing-job workflows, so an agent should not confuse them.

Naming Consistency4/5

Most tools follow a clean verb_noun convention: generate_logo, generate_color_palette, get_logo_result, search_blog, buy_logo_variation. The lone echo and the singular/plural mismatch between buy_logo_variation and generate_logo_variations are minor deviations from an otherwise consistent pattern.

Tool Count5/5

With 10 tools, the server is well scoped. The paid logo workflow is covered by generate, vary, buy, and retrieve tools, while supporting tools for palettes, SEO metadata, pricing, and blog search each serve a distinct purpose without bloat.

Completeness4/5

The core logo lifecycle is well covered: generate, create variations, purchase a variation, and retrieve the paid deliverable. However, the descriptions advertise upgrades and revision credits but provide no explicit tool to purchase or apply them, leaving a minor gap that agents must work around.

Resources