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

Annotations already declare readOnly, idempotent, non-destructive, closed-world, so the safety profile needs no restating. The description usefully discloses the shape of the result (a volume time series, not a summary), but says nothing about data freshness, resolution, or truncation for long windows. Adequate but thin beyond the 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?

Two sentences, zero filler. The capability statement comes first and the decision-support guidance second, so the agent gets the 'what' before the 'why'.

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?

For a two-parameter read tool with no output schema, the description covers the resource, the windows, and the intended interpretation of the returned series. It omits any note on result granularity or window limits, which is the only remaining gap.

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%: both period (with enum and default) and trend_id (with provenance from list_trends/search_trend_insights) are already documented. The description restates the three period values but adds no semantics the schema lacks, so the baseline 3 applies.

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: 'Get one trend's volume time series', plus the exact lookback windows supported. It is clear what is returned, but it never names or contrasts the sibling tools it could be confused with (get_trend, get_trend_ai_insights), so an agent must infer the boundary from the names alone.

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?

Explicitly frames the decision the tool supports ('tell whether a trend is still rising, flat or fading') and gives a concrete downstream use ('before deciding on campaign timing or budget'). There is no when-not-to-use or named alternative, which keeps it short of a 5.

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