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Niruchie

gemini-vision-mcp

by Niruchie

from_resources

Describe multiple URLs using Gemini by specifying media type and prompt. Send a list of resources to analyze text, images, audio, or video.

Instructions

Alias for vision_from_resources — describe multiple URLs using Gemini.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYesMedia category — text, image, audio, or video.
promptYesInstructions to the model (what to describe/extract).
compactNoIf true, compact history and reconnect after this request.
resourcesYesList of URLs to fetch.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description carries the full burden. As an alias it discloses that it uses Gemini, but it does not describe what happens to the resources (are they all sent simultaneously? Is there a size limit? Does compact affect behavior?). The description mentions 'describe multiple URLs' but gives no behavioral detail beyond the schema already provides.

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 description is a single efficient sentence. It's front-loaded with the essential purpose. However, as an alias it's arguably too sparse given the complex sibling landscape, but for pure conciseness it scores well — no wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has 4 parameters, an output schema, and lives among 13 siblings including near-identical naming patterns (from_file, from_files, from_resources, from_resources_mixed). An alias description that merely references another tool is inadequate for an agent to confidently select this one. There's no guidance on what distinguishes this alias from the canonical tool or from variants like from_resources_mixed.

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?

Schema description coverage is 100%, so the schema fully documents all 4 parameters (type, prompt, compact, resources). The description adds minimal value — it confirms 'multiple URLs' maps to the resources array, but this is already stated in the schema. With full coverage, baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description says it's an 'Alias for vision_from_resources — describe multiple URLs using Gemini.' It identifies the tool as describing multiple URLs, but as an alias it does not stand on its own as a purpose statement — it merely points to another tool. The verb 'describe' and resource type (URLs) is specified, but the primary function is delegated to a different tool name, which weakens self-contained clarity.

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

Usage Guidelines2/5

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

No guidance on when to use this alias vs. the canonical vision_from_resources or when to choose from_resources over from_files/from_resource. With a crowded sibling set (from_resources, from_resource, from_files, from_resources_mixed, etc.), the description offers no differentiation. It simply asserts it's an alias without adding when-to-use context.

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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