Staan answer

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

Annotations already declare readOnly, non-destructive, open-world and non-idempotent behavior, so the description's main added value is disclosing that the answer is synthesized by another LLM and backed by citations. That explains the non-determinism behind idempotentHint=false and sets expectations for output shape, though it says nothing about latency, cost, or accuracy limits of the generated answer.

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?

Two sentences, zero waste, with the core purpose front-loaded before the sibling-routing guidance. No restatement of the title or redundant phrasing.

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?

With a 100%-covered schema, an output schema, and full annotations, the description only needs to frame the tool's role, which it does. Minor gap: it doesn't mention the short/long answer or simple_response truncation of the response, which affect what the agent will actually receive.

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?

Schema description coverage is 100%, so every parameter, enum default and the nested source object are already documented in structured data. The description only gestures at 'sources you supply' and 'web pages'; it adds no syntax, limits (e.g. 10-source cap) or interaction detail such as how filter and sources conflict. Baseline 3 is appropriate.

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?

States a specific verb+resource ('Answer a question') and the defining output trait ('with citations, grounded in web pages or in sources you supply'). It also explicitly separates itself from its only sibling: 'Use it instead of web_search when you want a ready answer created by another LLM.'

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?

Names the alternative (web_search) and the condition that selects this tool ('when you want a ready answer created by another LLM'), which is a clear routing rule. It stops short of stating the inverse case (e.g. use web_search when you need raw result lists), so it is strong but not a full when/when-not rubric.

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