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

Annotations already declare the safety profile (readOnly, idempotent, non-destructive), so the bar is lower. The description adds valuable behavioral context the annotations cannot: results are daily-granularity, and the tool computes a directional half-over-half verdict rather than just returning raw numbers. It omits any note on history limits, but the schema covers that.

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 output shape (daily metrics + comparative verdict) comes first and the motivating question comes second, which is the right front-loading for a retrieval tool.

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 usefully sketches what comes back (daily engagement/impressions plus an improvement verdict), covering the main unknown. Minor gaps remain around scoping defaults and history limits, but those live in the schema, so an agent has enough to call it correctly.

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 the schema fully documents days, accountId, and workspaceId including the 365-day cap and scoping precedence rules. The description mentions "over the period" only implicitly; per the calibration baseline, 3 is correct when the schema does the heavy lifting.

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 names a specific resource and metric (daily engagement and impressions) plus a distinctive derived output (second-half vs first-half comparison), so the agent knows this is a trend tool, not a raw dump. It stops short of naming the closest siblings (get_analytics, get_follower_growth), so differentiation is inferential rather than explicit.

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 it to answer 'are we improving?'" gives a genuine usage scenario, which is more than most analytics tools offer. However, it gives no when-not guidance and never mentions get_analytics, get_follower_growth, or get_best_times, so the agent must guess which analytics sibling fits.

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