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vision.inspect

Identify objects, text, or anomalies in a local image by specifying a task. Get structured JSON results from AI vision analysis.

Instructions

Analyze a local image file with the Qwen3-VL vision model. Returns structured JSON with the vision analysis.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
taskYesWhat to look for / what the vision model should analyze.
image_pathYesAbsolute path to the image file on this machine.
Behavior4/5

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

No annotations are provided, so the description carries the burden. It clearly states the tool analyzes the image and returns structured JSON, revealing the output behavior. It doesn't mention side effects, but as a read-only analysis tool, minimal disclosure is acceptable.

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 sentences, front-loads the action, and avoids unnecessary detail. Every word adds value.

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 tool with two parameters and no output schema, the description gives a reasonable overview: it specifies local file input and JSON output. It doesn't detail the vision analysis structure, but given the tool's simplicity, it's adequately complete.

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?

The schema already describes both parameters fully with 100% coverage. The description does not add any additional parameter-specific semantics, so it meets the baseline of 3 for schema-covered parameters.

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 uses a specific verb 'Analyze' with the resource 'local image file' and names the exact model 'Qwen3-VL vision model'. It also states the output type, making it clear what the tool does. No siblings exist, so differentiation isn't needed.

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

Usage Guidelines4/5

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

The description indicates the tool operates on 'local image file', setting a clear context for local paths. It doesn't mention alternatives or exclusions, but with no sibling tools this is acceptable. The context of local file analysis is implicit but clear.

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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