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

Annotations already establish read-only/idempotent/non-destructive behavior, but the description adds substantive context beyond them: the control-group subtraction to remove seasonality and Google-update noise, the watch-history enrichment, and an explicit data-handling statement that numbers are used for this answer only and not stored.

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?

Dense but front-loaded, leading with the payoff question before the mechanics. It is a long single block of prose, yet nearly every clause carries actionable information about inputs or method.

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 output schema covers return values, so the description only needs to explain inputs, method and caveats — which it does. Data preparation, detrending rationale, watch_id enrichment and privacy are all addressed, leaving no obvious gap for correct invocation.

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?

With 60% schema coverage, the description compensates well: it explains the two-period design behind before/after, the meaning of changed=true/false and the control group, a suggested value for days, and the role of watch_ids in listing per-page changes. It adds real meaning beyond the raw schema.

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 outcome ('Show whether SEO fixes paid off') plus the mechanism (before/after periods from connected tools, control-group detrending). This is clearly distinguishable from siblings like get_watch or rescan_and_compare, which track or re-scan rather than quantify impact.

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 concrete operating instructions: fetch two equal-length periods (28 days suggested) from GSC/GA4/Ahrefs/Semrush, include changed=true pages plus an ideal control group, and pass watch_id to see what changed. It stops short of naming when NOT to use it or which sibling to prefer instead.

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