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

Annotations already declare readOnly and closed-world, but the description adds a genuinely non-obvious behavioral trait: the series is sparse, and days with no runs are absent rather than zero. The explicit warning never to read a missing day as 0% placement is exactly the kind of semantics annotations cannot convey.

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?

Three tight sentences, front-loaded with the core operation and its default, then the crucial sparse-series caveat. No filler; every sentence carries load.

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 carries the return-value burden and does so by describing the shape of the series and its absence behavior. An agent can both call it correctly and interpret the result without guessing.

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%, so both parameters (from/to) are already documented with RFC3339 format and defaults. The description restates the 30-day default and adds the UTC-day bucketing concept, but adds little else beyond what the schema provides. 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 (rolls up), resource (completed inbox placement runs), aggregation dimension (UTC calendar day), and purpose (trend). This cleanly separates it from the raw-run siblings like list_inbox_placement_runs and get_inbox_placement_run, which return individual runs rather than an aggregated series.

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?

Gives clear context (use it for a trend) and states the window default of the last 30 days. It does not name an alternative tool or give explicit when-not-to-use conditions, but the trend framing makes the intended use unambiguous.

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