search_statistics

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, covering the safety profile. The description usefully adds the content boundary (returns only hard numbers, not narrative) and the cross-graph scope (domain, specialist, report graphs). It doesn't address the notable idempotentHint=false or result format, so a 4 rather than 5.

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?

Three tightly packed sentences that are front-loaded with the core purpose before exclusions and sibling routing. Every clause earns its place; no filler.

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?

No output schema exists, but the description fully explains what comes back (figures, percentages, market sizes, growth rates linked to parent trends) and what does not. Combined with rich annotations and a fully documented schema, an agent has everything needed to call it correctly.

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 already documents all seven parameters including sector scoping, graph_id, min_score thresholds, and limit. The description adds no parameter-level detail (e.g., how sector interacts with graph_id beyond what the schema says), so the baseline 3 applies.

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 content type ('quantitative statistics and hard numbers layer only') and enumerates what it returns: figures, survey percentages, market sizes, growth rates. It explicitly distinguishes itself from siblings like search_insights and get_domain_intelligence, so an agent can identify it without opening the schema.

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?

Provides explicit when-not guidance ('Does NOT return narrative analysis, trends, or quotes'), names the correct alternatives for those cases (search_insights, get_domain_intelligence), routes company/brand queries to brand_tracker, and gives ordering advice ('Try this before external supplemental data tools'). Full routing decision is encoded.

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