google_lens_detect

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

No annotations are provided, so the description carries the full burden. It explains the internal process (OpenCV detection, cropping, sending to Google Lens) and that it returns identification results for each object. However, it does not disclose error handling or behavior when no objects are detected, which is a gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with clear sections: overview, step-by-step process, use cases, supported formats, and sample prompts. Every sentence adds value without redundancy.

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

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

The description covers purpose, usage, parameter details, and sample prompts. Since an output schema exists, not explaining return values is acceptable. Missing error handling or performance notes, but overall fairly complete for a single-parameter tool.

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

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

The schema has 0% description coverage, but the description adds value by stating that image_source supports local file paths and base64-encoded image data, going beyond the schema's type definition.

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

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

The description clearly states the tool detects and identifies all objects in an image using OpenCV and Google Lens. It distinguishes itself from the sibling tool google_lens by detailing the multi-step process (detect, crop, send both original and crops).

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

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

The description explicitly compares with google_lens and provides sample prompts that illustrate when to use this tool (e.g., multiple items in an image). It also mentions supported input types (local paths and base64), giving clear context for use.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.