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recognize_image

Recognize and describe the content of local images using a multimodal model. Provide an optional prompt to guide the description.

Instructions

Recognize and describe an image using a multimodal model (Kimi K2.5). Returns a text description of the image content.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptNoOptional instruction to guide the recognition, e.g. 'extract all text', 'describe the UI layout', 'what code is shown'
image_pathYesAbsolute path to the local image file
Behavior2/5

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

No annotations are provided, so the description must disclose all behavioral traits. It only mentions the model and that it returns text, but lacks details about file format support, size limits, network requirements, or latency.

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 very short and to the point. While it is concise, it could benefit from a bit more structure or detail without becoming verbose.

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?

For a tool with no annotations or siblings, and only two parameters, the description is insufficient. It lacks information about return values, error handling, or typical use cases.

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 coverage is 100%. The description adds no extra meaning beyond the schema's parameter descriptions. Baseline score of 3 applies.

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

Purpose4/5

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

The description clearly states the action (recognize/describe) and the resource (image using a specific model), making the purpose obvious. However, it does not distinguish from potential siblings, but no siblings are listed.

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 tool versus alternatives. It does not provide any context about prerequisites, limitations, or when it should not be used.

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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