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

Annotations already declare read-only, idempotent, non-destructive behavior. The description adds valuable context beyond that: it will not invoke a tool call and instead returns step-by-step guidance for fixing losing day-parts. It does not describe data freshness or output shape, but the output schema covers return structure.

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 purpose is front-loaded and the description is only a few sentences. The trailing 'Tools revision' line is metadata noise that does not help an agent decide or invoke the tool, but the rest is efficient.

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?

The description is adequate for understanding the analytical intent and the no-tool-call behavior, and the output schema handles return values. However, with five parameters at 0% schema description coverage, the definition is incomplete on how to configure the analysis.

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 0%, so the description must carry the burden. It does not explain the days, detail, render, max_findings, or customer_id parameters, aside from an implicit 90-day default. An agent cannot learn from the description how to control scope, detail level, or output rendering.

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 analytical operation: breaking 90 days of cost, conversions, and CPA down by day of week and hour, and identifying money-losing and underserved day-parts. It clearly distinguishes this diagnostic tool from the sibling mutation tool set_ad_schedule by noting that it only provides steps and returns no tool call.

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?

It gives clear implied usage context: use this to diagnose day-part performance and get guidance for schedule changes. It also implicitly routes agents to set_ad_schedule for actually applying changes. It does not explicitly state when not to use this versus other analysis tools like analyze_waste or bidding_audit.

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