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google_lens

Retrieve product results, visual matches, and exact matches from Google Lens for a given image URL.

Instructions

Reverse image search via Google Lens, supporting product results, visual matches, and exact matches for a given image URL. Costs 5 API credits per request. [Credits: 5 API credits per request] Notes: Documented parameter type for product/visual_matches/exact_matches is String but values are boolean-like ('true'/'false'). Returns: { lens_results: [{position, title, source, link, thumbnail}] }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesThe Google Lens URL to scrape, typically in the form https://lens.google.com/uploadbyurl?url={image_url}.
queryNoAdditional search query to execute alongside the reverse image search, same as a standard Google search. Example: query=pizza
countryNoISO 3166-1 country code for Google Lens results. (default: us)
productNoSet true to retrieve product results from Google Lens. (default: false)
languageNoLanguage of the results, e.g. en, es, fr, de. (default: en)
exact_matchesNoSet true to retrieve exact match results from Google Lens. (default: false)
visual_matchesNoSet true to retrieve visual match results from Google Lens. (default: false)
Behavior4/5

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

Discloses cost (5 API credits), parameter type nuance (string but boolean-like), and returns structure. With no annotations, this is valuable behavioral context. Lacks mention of idempotency or rate limits, but sufficient for a search tool.

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?

Concise and front-loaded with the main action and credits. Could be more structured (e.g., bullet points), but no wasted sentences.

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?

Given 7 parameters with 100% schema coverage and no output schema, the description provides meaningful extra context (credits, type warning, return format) to support agent decision-making. Complete enough for typical use.

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

Parameters4/5

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

Schema coverage is 100%, but description adds clarity on boolean-like parameter values and the URL format for the required parameter. This goes beyond the schema descriptions, aiding correct usage.

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?

Description clearly states it performs reverse image search via Google Lens, supporting product, visual, and exact matches. It differentiates itself from sibling tools like google_search and google_images by specifying the Lens endpoint and result types.

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, such as when to choose Lens over generic image or web search. No explicit when-not-to-use scenarios mentioned.

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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