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ai_search_web

ai_search_web

Search the web using Google, Bing, Baidu, or Sogou to find relevant information and generate search result URLs for further processing.

Instructions

🔍 网络搜索 - 通用网络搜索(Google/Bing/百度/搜狗)

【重要】此工具会返回搜索URL,Claude Code应该使用WebFetch工具访问该URL以获取真实搜索结果。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
engineNo
countNo
Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses that the tool returns search URLs rather than actual content, and that a separate WebFetch tool is needed to get results. However, it doesn't mention important behavioral aspects like rate limits, authentication needs, error handling, or what format the URLs are returned in. The description adds some value but leaves significant gaps for a tool with 3 parameters and no output schema.

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?

The description is appropriately concise with two sentences. The first sentence clearly states the purpose with emoji and engine list. The second provides important implementation guidance. Both sentences earn their place, though the structure could be slightly improved by front-loading the most critical information more explicitly.

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 3 parameters with 0% schema coverage, no annotations, no output schema, and many sibling tools, the description is incomplete. It doesn't explain parameter usage, return format, error conditions, or differentiation from specialized search siblings. While it provides the crucial insight about URL returns requiring WebFetch, this alone is insufficient for a tool of this complexity and context.

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

Parameters2/5

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

With 0% schema description coverage and 3 parameters (query, engine, count), the description provides no information about any parameters. It doesn't explain what the 'engine' parameter accepts (presumably one of the listed search engines), what 'count' controls (number of results?), or any formatting requirements for the 'query'. The description fails to compensate for the complete lack of schema documentation.

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 performs '通用网络搜索' (general web search) and lists specific search engines (Google/Bing/百度/搜狗), which provides a specific verb+resource. However, it doesn't explicitly differentiate from its many sibling tools that appear to be specialized searches (docs, API references, specific platforms), leaving some ambiguity about when to choose this general tool versus the specialized ones.

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

Usage Guidelines3/5

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

The description implies usage through the instruction that Claude Code should use WebFetch to access returned URLs, providing some context about how results are obtained. However, there's no explicit guidance on when to use this tool versus its many specialized sibling tools (like ai_search_docs, ai_search_github, etc.), nor any mention of alternatives or exclusions.

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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