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find_similar_in_folder

Scan a folder and rank images by visual similarity to a reference image using mathematical feature comparison.

Instructions

Find visually similar images in a folder.

Scans all images and ranks them by visual similarity to the query. Similarity is based on mathematical features, not semantic content.

Args: query_image: Path to the reference image folder_path: Folder to search top_k: Number of results (1-20) feature: Feature for comparison - "JCD", "CEDD", "ColorHistogram", etc.

Returns: Ranked list of similar images with scores.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
query_imageYes
folder_pathYes
top_kNo
featureNoJCD

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations provided, so the description carries full burden. It explains that similarity is based on mathematical features not semantic content, and that it scans all images. However, it does not disclose potential side effects, error handling, or whether the operation is read-only. Adequate but not comprehensive.

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 concise and well-structured: purpose statement, brief explanation of method, list of parameters with descriptions, and a return summary. Every sentence adds value with no redundancy.

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?

The description covers the tool's purpose, parameters, and return value briefly but adequately. Given that an output schema exists, the return description is acceptable. Missing details like error handling or prerequisites, but overall sufficient for a straightforward tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, but the description compensates effectively with a clear Args section detailing each parameter's purpose, including examples for the 'feature' parameter and a range for 'top_k'. This adds significant meaning beyond the bare schema.

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 tool finds visually similar images in a folder and ranks them. It is specific with verb and resource but does not explicitly distinguish from sibling tools like compare_images or filter_by_vibe, though the context implies a difference.

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 explicit guidance on when to use this tool versus alternatives. The description only states what it does, leaving the agent to infer usage context. Given the presence of similar sibling tools, this is a gap.

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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