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

Annotations already mark the tool as read-only and non-destructive. The description adds further behavioral detail: timezone handling, click-hour attribution, data source (Marketing Stream), and the provisional-flag caveat. This is strong supplementary transparency 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?

The description is dense but every sentence earns its place: scope, output contents, attribution rule, timezone, and interpretational caveat. It is front-loaded with the core purpose and wastes no words.

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 read-only analytics tool with one optional parameter and no output schema, the description gives enough detail about return values, data source, timezone, and decision-making caveats. The agent can invoke it correctly and interpret results.

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 the optional profile_id and its behavior. The tool description does not add parameter-level meaning, matching the baseline for high coverage.

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 states a specific verb ('Returns') and resource ('Dayparting schedule AND real hour-of-day performance'), and enumerates exactly what is returned (7x24 bid-multiplier grid, hourly_performance, day-x-hour matrix). This clearly distinguishes it from schedule-editing siblings like stage_dayparting_schedule.

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 context for when to use this tool, particularly the caution about needing 21+ days of persistent pattern and respecting the provisional flag. It does not explicitly name alternatives or exclusions, but the usage context is clear.

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