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

Beyond the read-only, idempotent annotations, the description discloses the computation formula, return fields (hiddenShare, level, worst day, optional daily table), threshold semantics, and the searchType-only scope. That is strong behavioral context for an analysis tool.

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 core computation is front-loaded, followed by outputs, thresholds, and usage guidance. It is dense and slightly run-on, but every clause carries substantive information and nothing is redundant.

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 computation-heavy analysis tool with no output schema, the description supplies the formula, output fields, level thresholds, optional table behavior, and intended diagnostic use. It gives an agent enough to call the tool correctly and interpret the result.

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 the parameter details are already documented, but the description adds a meaningful semantic constraint: only searchType applies and dimension filters are not appropriate here. The optional daily table note also maps usefully to includeDaily.

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 computed resource: anonymization-hidden clicks/impressions, defined as exact daily totals minus summed query × page rows. It is clearly distinct from sibling query/page and summary tools, and it explains the reconciliation purpose rather than merely restating the tool name.

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 use cases: explain why top-query totals do not add up to summary totals, and check before trusting query-level shares on small sites. It also notes that only searchType applies, excluding dimension filters, but it does not name a specific alternative tool for those cases.

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