Get AI-powered answers with citations and reasoning. Use when you need synthesized answers rather than raw search results. Providers: kagi_fastgpt (fast ~900ms answers), exa_answer (semantic AI), linkup (deep agentic search with sources).

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

Annotations already declare readOnlyHint, destructiveHint, idempotentHint, and openWorldHint, covering safety and idempotency. The description adds context about provider speeds but does not expand on behavioral traits 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.

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

Description is front-loaded with purpose and differentiation, but contains redundant provider information that contradicts the schema, making it less concise and slightly misleading.

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?

Mentions that the tool returns answers with citations and reasoning, which is useful given no output schema. However, lacks details on output format, limitations, or what the 'reasoning' includes.

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?

Input schema has 100% description coverage for all three parameters. The description does not add any parameter-specific information beyond what is already in the schema.

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?

Tautological: description restates name/title.

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?

Provides good differentiation from siblings (synthesized vs. raw), but lists providers that are not available in the input schema, misleading the agent about which providers can actually be used.

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