web_search

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

No annotations are provided, so the description carries the full burden. It discloses that the tool returns an AI-generated answer based on full page content plus source URLs, and notes it is powered by DeepSeek's native web search API with server-side execution. This adds valuable behavioral context about output format and implementation. It doesn't mention potential limitations like rate limits or latency, but for a search tool this is reasonably transparent. A 4 is appropriate.

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

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

The description is moderately sized, provided bilingually, and well-structured with a clear separation of purpose, usage, and output. Every sentence contributes value, but the bilingual repetition (Chinese and English) makes it slightly longer than strictly necessary. Still, each part earns its place, so it is concise for a description that needs to serve both languages.

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

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

For a tool with only two parameters (one required) and no output schema, the description provides complete context: what it does, when to use it, what it returns (detailed AI answer + source URLs), and a hint for parameter usage. There is no ambiguity about the tool's operation or expected results, making it fully self-contained.

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

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

The input schema already covers both parameters with descriptions (100% coverage). The description adds extra guidance for the query parameter, advising the user to be specific and include relevant keywords. This goes beyond the schema by offering a practical tip for better results, which is helpful for an agent crafting effective search queries.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it searches the internet for current, real-time, or factual information, with a specific verb ('search') and resource ('the web'). It goes beyond a simple statement by listing concrete use cases (recent events, current data, documentation lookups, fact-checking), making the tool's purpose unmistakable even without sibling tools to compare against.

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

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

The description explicitly says to use this tool when information is needed beyond the training cutoff, and lists specific scenarios: recent events, current data, documentation lookups, or fact-checking. This gives clear when-to-use guidance, and the implicit contrast with 'training data' tells the agent when not to use it (for general knowledge already known).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.