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search_engine_batch

Execute multiple web searches concurrently across Google, Bing, and Yandex to gather real-time data for research and monitoring purposes.

Instructions

Run multiple search queries simultaneously. Returns JSON for Google, Markdown for Bing/Yandex.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queriesYes
Behavior2/5

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

With no annotations provided, the description carries full burden. It discloses output format differences (JSON for Google, Markdown for Bing/Yandex), which is useful behavioral context. However, it doesn't mention rate limits, authentication needs, error handling, or what 'simultaneously' entails (parallel vs sequential). For a batch operation tool, this leaves significant gaps in understanding its behavior.

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?

Extremely concise with two sentences that each add value. First sentence states core functionality, second sentence provides critical output format information. No wasted words, perfectly front-loaded with essential information.

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

Completeness2/5

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

Given no annotations, 0% schema description coverage, and no output schema, the description is incomplete for a batch search tool. It covers purpose and output formats but misses parameter explanations, error conditions, rate limits, and detailed behavioral traits. For a tool handling multiple search engines with different output formats, more context is needed.

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 description coverage is 0%, so the description must compensate. It adds some meaning by mentioning engine-specific output formats, which relates to the 'engine' parameter. However, it doesn't explain the 'queries' array structure, 'cursor' parameter purpose, or the 1-10 item limit. The description provides partial context but doesn't fully compensate for the schema's lack of descriptions.

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's purpose: 'Run multiple search queries simultaneously' specifies the verb and resource. It distinguishes from siblings like 'search_engine' (likely single query) and 'scrape_as_markdown'/'scrape_batch' (different operations), though not explicitly named. However, it doesn't fully differentiate from 'scrape_batch' which might also handle multiple items.

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 is provided. The description mentions output formats for different engines, but doesn't state when to choose this batch tool over single-query tools like 'search_engine' or scraping tools. Usage context is implied but not clearly defined.

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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