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

Annotations already cover readOnly/idempotent/openWorld, yet the description still adds non-obvious traits: ~30 s live latency, per-call price of $0.045, the rule that bad input and upstream errors are free but success is charged, and the x402/USDC-on-Base payment path via _meta["x402/payment"]. That is exactly the operational context an agent needs before spending money.

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?

Four tight sentences front-loaded with what the tool returns, then when to use it, then granularity, latency and pricing. No filler, and the cost/payment caveat is placed where an agent will see it before calling.

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 no output schema, the description still specifies the return shape (dated 0-100 series), the resolution per timeframe, and the full cost/payment model. There is no material gap an agent would need to close before invoking it.

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 country codes, keyword length limits and the timeframe enum are fully documented in the schema. The description only reinforces the single-keyword constraint and states the daily-vs-weekly granularity split, adding modest value above the baseline.

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 opens with a specific verb+resource ('Google Trends interest over time for one keyword') and defines the returned shape as a dated 0-100 series with country/worldwide scope. The 'one keyword' phrasing distinguishes it in spirit from google_trends_by_region and google_trends_related_queries, though those siblings are never named, so an agent must infer the boundary.

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?

'Use when you need search-interest trends, seasonality or demand direction for a keyword' gives clear positive selection criteria. It stops short of exclusions or explicit alternatives (e.g., 'use google_trends_by_region for a regional breakdown'), leaving that routing to inference.

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