google_ai_mode

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

With no annotations provided, the description carries full burden and excels. It discloses unreliability, confident wrongness, the risk of false authority on Google products, the meaning of absent results (available: False vs error/schema_drift), and the slower streaming/polling behavior. This is far beyond a generic tool disclaimer.

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 longer than necessary but every paragraph and warning earns its place. It is front-loaded with the core purpose, then structured warnings, normal-use pattern, absence behavior, and latency. Bolded headings aid scannability. Slight verbosity prevents a 5.

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?

Given no output schema and no annotations, the description is remarkably complete. It conveys what the response contains (answer + citations), how to interpret the answer, what absence looks like, and latency expectations. The tool's complexity is high, and the description covers the key edge cases (missing availability, unreliability, comparison to sibling tool) without needing structured output docs.

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 0%, so the description must compensate for parameter ambiguity. While 'query' is implicitly described, there is no explanation of the lang or country parameters, their allowed values, defaults, or how they affect results. The mention of region/account relates to availability, not parameter semantics, leaving optional parameters under-specified.

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 returns Google's AI Mode answer with citations, using a specific verb ('answer') and distinct resource. It distinguishes itself from google_search by positioning AI Mode as an unreliable lead-generation tool, and it explicitly names google_search as the alternative for authoritative sources.

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 gives explicit usage guidance: use for orientation on unfamiliar topics, then follow up with google_search for primary sources, and skip for anything load-bearing. It clearly states when not to use it and names the alternative tool, satisfying the highest bar for this dimension.

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