Research Web

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

Annotations already declare readOnlyHint and openWorldHint, so safety is covered. The description adds genuinely useful context beyond them: fixed high thinking level (cost/quality tradeoff) and latency varying with query and provider load. It stops short of saying anything about failure modes, cost, or rate limits for an open-world call.

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?

Front-loaded with the core behavior and return shape, then one line on quality/latency, then a trigger list. Efficient overall; the latency sentence is arguably secondary but earns its place as a cost signal.

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?

An output schema exists, so return-value detail is unnecessary, and annotations cover the safety/open-world profile. The description is complete enough to call correctly; only the relationship to the deep/compare siblings and any cost expectations are left unstated.

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 coverage is 100% with only two parameters, both documented in the schema, so the baseline is 3. The description adds no meaning to either parameter — notably it says nothing about when a caller would want include_thoughts, nor how the query should be phrased (question vs keywords) for grounding.

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 and resource ("Web research with Gemini grounding. Returns an answer with citations") and adds that it uses "a fixed high thinking level". It implicitly contrasts with the deep/deep_max siblings that presumably vary thinking level, but never names them, so sibling differentiation is only inferable.

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 "Use for:" list gives concrete, recognizable triggers — quick lookups, fact-checking, current events, docs, error messages, news. It lacks any when-not guidance or explicit pointer to research_deep / research_compare for heavier or comparative work, so the agent must guess at the escalation path.

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