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OpenWeb-Ninja

OpenWeb Ninja MCP

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ai_overviews

Retrieve Google's AI Overview answer block for any search query to get summarized insights directly.

Instructions

Fetch Google's AI Overview answer block for a search query.

Operations (set "operation" to one of these; put its parameters in "args"):

  • ai_overviews (required: q): AI Overviews

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
argsNoParameters for the chosen operation as key/value pairs (see the tool description for required params).
operationYesWhich endpoint to call. See the tool description for each operation and its parameters.
Behavior2/5

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

Annotations are absent, so the description carries the full burden. It discloses the basic read behavior but does not mention rate limits, authentication, response format, error handling, or what happens when no AI Overview exists. The generic operation structure is also not explained beyond the minimal contract.

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 extremely concise, front-loaded with the main purpose, and includes only the essential operation details. No filler or redundant content.

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?

For a simple single-operation tool with no output schema, the description provides the minimum viable information. It lacks guidance on expected output, use cases versus siblings, and any limitations, leaving gaps for an AI agent deciding between this and similar search tools.

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?

The schema descriptions for 'operation' and 'args' are generic and reference the tool description. The description adds value by specifying the exact operation value ('ai_overviews') and noting that 'q' is required, which clarifies the search query parameter. It could be improved by explicitly defining 'q' as the search query.

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 fetches Google's AI Overview answer block for a search query, which is a specific verb and resource. However, it does not explicitly differentiate from similar sibling tools like google_ai_mode or realtime_web_search, so it falls short of a 5.

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 is given on when to use this tool versus alternatives such as google_ai_mode, gemini, or realtime_web_search. The description only states what it does and how to call it, with no exclusions or preferred scenarios.

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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