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crop_for_inspection

Crop a specific region of an image to zoom in for detailed inspection, enabling precise coordinate identification by vision models. Supports pixel or normalized coordinates with optional padding.

Instructions

Crop a region of an image and save it to a new file. Useful for iteratively zooming into a region so a vision model can give more precise coordinates. Bounding box can be in pixel or normalized [0, 1] coordinates; optional padding expands the crop on each side.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bboxYes
pathYes
paddingNo
normalizedNo
output_pathNo
Behavior3/5

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

Annotations are absent, so the description must carry the burden. It discloses bounding box coordinate systems and padding, which is helpful. However, it omits behavioral details such as what happens when output_path is null (e.g., default save behavior or return value) and whether the original file is preserved. This gap reduces transparency.

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 highly concise (three sentences) and front-loaded with purpose, then use case, then details. Every sentence adds value without redundancy.

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

Completeness3/5

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

Given the tool has 5 parameters, no output schema, and no annotations, the description covers the overall purpose and a key use case but lacks full parameter documentation (e.g., output_path behavior and normalized boolean). It is adequate for simple usage but not fully complete for an agent to confidently invoke without additional assumptions.

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 0%, so the description must compensate. It explains bbox (pixel or normalized) and padding, adding meaning beyond the schema. However, it does not describe the normalized boolean parameter directly (only alludes to it), nor the behavior of output_path being null. Some parameters remain unexplained, leading to a moderate score.

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 verb (crop), resource (image), and action (save to new file). It also provides a specific use case ('iteratively zooming into a region so a vision model can give more precise coordinates') that distinguishes it from sibling tools like annotate or draw_bounding_box.

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 gives a clear context for when to use the tool (iterative zooming for vision models) but does not explicitly exclude alternative tools or mention when not to use it. The context is clear enough for simple cropping tasks.

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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