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minimax_understand_image

Understand image content by asking questions about it. Supports image URLs, local files, or base64 data up to 20MB.

Instructions

Analyze an image using MiniMax AI vision. Supports URLs, local file paths, or base64 data URLs (JPEG/PNG/WebP, max 20MB).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesQuestion or instruction about the image
imageSourceYesImage URL (HTTP/HTTPS), local file path, or base64 data URL
modelNoModel override (default: MINIMAX_DEFAULT_MODEL env var, typically M2.7)
Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses supported image formats and size limits, and mentions the model override capability. However, it does not state whether the operation is read-only, what the output type is (e.g., text), or behavioral nuances like error handling or idempotence.

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 two essential sentences: the first states the core purpose, and the second provides key constraints on inputs. No redundant text. It is front-loaded with the main action and uses efficient wording.

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?

Despite having no output schema, the description omits any mention of what the tool returns (e.g., a text description, analysis results, or error messages). It also does not address prerequisites, potential errors, or limitations beyond format and size. This gap is significant for an image analysis 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 baseline is 3. The description adds value by specifying valid input formats for imageSource (URLs, local paths, base64, with format and size constraints), which goes beyond the schema's generic 'Image URL' description. For prompt and model, the description adds little beyond the schema, but the extra detail on imageSource justifies a 4.

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 purpose: 'Analyze an image using MiniMax AI vision.' It distinguishes from sibling tools like minimax_chat and minimax_generate_code by specifically focusing on image analysis, and the mention of supported input formats further clarifies its scope.

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?

The description provides no guidance on when to use this tool versus alternatives such as minimax_agent_task or minimax_chat. It does not specify use cases, prerequisites, or exclusions, leaving the agent to infer suitability from the tool's name and basic function.

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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