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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false, so 'Read-only.' is redundant. However, the description adds genuinely useful behavior: results are structured per check as a problem with its fix and tools, ok, or unknown, and checks reference external data (Analytics paid_vs_other, the account's own 90-day baseline). That output-shape and data-dependency disclosure goes beyond what the annotations provide.

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 verb and scope are front-loaded, and each enumerated check is informative for judging coverage. But it is a single ~130-word run-on sentence with no list structure, which makes it hard to scan; a bulleted list or a short summary plus detail would earn the same information in less cognitive 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?

There is no output schema, and the description compensates by explaining the per-check result shape (problem + fix + tools, ok, unknown). Combined with the exhaustive enumeration of checks and the read-only/idempotent annotations, an agent has enough to decide and call correctly. Cost/time expectations for what is clearly a broad multi-source diagnostic are the only notable omission.

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?

Only one parameter, and the schema documents it at 100% coverage ('Client name from list_clients'). The description's 'a client's Google Ads account' restates the same meaning without adding format, validation, or resolution behavior. High schema coverage makes 3 the correct baseline.

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 (check) and resource (client's Google Ads account) and enumerates the exact categories examined: conversion tracking, bidding, lost search impressions, keyword quality, ad strength, search terms, conversion-rate baseline, cross-channel paid comparison, search-term intent, exact negatives, and landing pages. That is far beyond tautology and lets an agent see the scope. It stops short of explicitly differentiating itself from near siblings such as audit_client, ads_report, or autopilot_run.

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 phrase 'the way Autopilot must before saying nothing needs changing' implies a usage context (pre-flight/health check before declaring an account healthy), but it is only implied. No when-not conditions and no named alternatives are given, so an agent must infer whether to pick this over audit_client or ads_report.

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