Web Search

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

The description adds useful context beyond annotations: cost estimates, recommendation to increase timeout for complex queries, and that results include source URLs. However, it does not clarify the non-read-only nature (readOnlyHint=false) or any side effects, leaving some behavioral traits implicit.

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 concise: a clear opening sentence, bullet points for use cases and tips, and a cost note. It is front-loaded with purpose and well-structured, with no redundant sentences.

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 9 parameters and no output schema, the description covers purpose, use cases, cost, and practical tips. It could mention result pagination or format details, but overall it provides sufficient context for an AI agent to use the tool effectively.

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?

All 9 parameters have schema descriptions (100% coverage). The description adds practical usage guidance for maxResponseLength, timeout, and effort, helping the agent understand how to use them effectively beyond what the schema provides.

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 the tool performs web search via Claude Code CLI and synthesizes a comprehensive answer with source URLs. It is distinct from sibling tools like listSessions, ping, query, and structured, which serve different purposes.

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 lists use cases (e.g., current information, documentation lookups) and provides tips (e.g., ask specific questions, use maxResponseLength). It does not specify when not to use or compare directly with alternatives, but the context is clear enough for appropriate selection.

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