Skip to main content
Glama

check_image_cultural_fit

Analyze an image for cultural-sensitivity issues across markets before launch.

Returns a SAFE / NOT SAFE verdict and, where relevant, the specific
countries affected with the issue and a concrete fix.

Args:
    image_path: Public HTTPS URL (hosted) or local path (stdio) to a PNG, JPEG, or WebP image.
    countries: Optional comma-separated list of countries to check against
        (e.g. "Saudi Arabia, Japan, France"). Defaults to the top markets by GDP.

Input Schema

NameRequiredDescriptionDefault
countriesNo
image_pathYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It does disclose the output shape (SAFE / NOT SAFE, affected countries, concrete fix), but says nothing about cost, latency, image size limits, authentication requirements, or whether the verdict is deterministic — gaps that matter for a judging tool an agent may call repeatedly.

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?

The verdict/return summary is front-loaded and the Args block is tight and scannable. Minor redundancy in restating return values already covered by the output schema, but nothing that wastes the reader's attention.

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?

For a two-parameter read-style tool with an output schema and no annotations, the definition covers inputs and outputs adequately. The remaining omission is operational context — limits, latency, or failure modes — which would matter for repeated or batch use but is not blocking for a correct single call.

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

Parameters5/5

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

Schema coverage is 0%, yet the description fully compensates: image_path is defined as a public HTTPS URL on hosted transport or a local path on stdio, with accepted formats (PNG, JPEG, WebP); countries is defined as a comma-separated list with a worked example and an explicit default (top markets by GDP).

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?

States a specific verb and resource — 'Analyze an image for cultural-sensitivity issues across markets' — plus the decision it supports ('before launch'). The domain is narrow enough that it is unambiguously distinct from siblings like localize_image or extract_image_text.

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?

'Before launch' implies a pre-release review workflow, which is useful timing context. However, there is no explicit when-not guidance, no prerequisites, and no named alternative for related needs (e.g., localize_image vs. this check), so the agent must infer routing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.