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Run a multi-engine web search and get a ranked, deduplicated list of links. Optionally translate results to any language.

Instructions

Run a multi-engine web search and return a ranked, deduplicated link list.

Args: translate_to: 翻译目标语言(例如 "zh", "en", "ja")。需要启用 LLM。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
enginesNo
max_resultsNo
pageNo
page_sizeNo
sort_byNo
translate_toNo
use_cacheNo
max_age_hoursNo
freshnessNo
include_domainsNo
exclude_domainsNo
categoryNo
include_textNo
exclude_textNo
formatNomarkdown

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

Annotations already provide readOnlyHint=true. The description adds behavioral details: results are 'ranked' and 'deduplicated', and it mentions multi-engine aggregation. However, it omits other traits like pagination behavior, rate limits, or whether the cache is automatically used, which would add value beyond annotations.

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

Conciseness2/5

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

The description is very short (one sentence plus a parameter note). While it front-loads the main purpose, it is too sparse given the tool's complexity (16 parameters). It sacrifices too much detail for brevity, making it insufficient for correct invocation.

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?

Despite having an output schema (which covers return values), the description lacks explanations for most parameters. The tool has 16 parameters and moderate complexity, but the description only addresses one parameter and the general function, leaving significant gaps for correct usage.

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

Parameters1/5

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

Schema description coverage is 0%. The description only explains one parameter (translate_to) with a Chinese note about needing LLM. The other 15 parameters (engines, max_results, page, sort_by, etc.) have no explanation, leaving the agent without understanding their meaning or 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?

The description clearly states 'Run a multi-engine web search and return a ranked, deduplicated link list.' It uses a specific verb ('run') and resource ('multi-engine web search'), and distinguishes from siblings like image_search or video_search by focusing on web search with multiple engines.

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 like research or semantic_search. It does not mention prerequisites, exclusions, or context such as when caching applies. The annotation openWorldHint=true hints at open-ended queries but is not explicit in the description.

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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