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

Annotations already declare readOnlyHint/idempotentHint/destructiveHint=false and a closed-world scope, so the safety profile is covered. The description adds real value by clarifying that statistics are computed only over *vorhandener* (present) values and that provenance/duplicate-ID checking is part of the behavior. It does not say whether duplicates cause rejection or deduplication, nor what the result looks like.

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?

Two dense sentences with no filler: capability statement first, capability exclusions second. Every clause carries information an agent cannot get from the schema or annotations.

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 tool with a nested two-object schema, no output schema and zero field documentation, the description covers purpose and exclusions but leaves the input contract largely unexplained. The most consequential ambiguity — whether duplicate or missing-provenance entries abort the call or are silently handled — remains unresolved.

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% and all field names are undocumented, yet the description only hints that rating and review_count feed the aggregation. The four required context fields (service, search_location, surface, observed_at) and their role as provenance inputs are never explained, nor is how id/observed_at are validated.

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 verb+resource combination: it validates the provenance and duplicate IDs of a *supplied* local competitor dataset and computes min/median/max over the ratings and review counts present in it. That distinguishes it reasonably well from data-gathering siblings, though the boundary against compare_business_profiles is not drawn explicitly.

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 explicit negative scope — no live Maps query, no review-authenticity check, no claim about the market minimum — which steers an agent away from misusing it. What is missing is positive routing: it never names which sibling to use when a live lookup or a profile comparison is actually wanted.

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