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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds minimal behavioral context: it clarifies the output is a count per region, but does not disclose pagination, data freshness, or other runtime behavior. No contradiction with annotations.

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 description is a single sentence (plus a bilingual duplicate) with zero waste. The core information is front-loaded: what the tool lists and what it reports. Nothing extraneous.

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 parameterless list tool with a clear purpose and no output schema, the description is complete. It states exactly what is returned: regions of Belarus with the number of open procurements. An agent can call it correctly without further context.

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?

There are no parameters, so the description does not need to explain any. Per the rubric, 0 params earns a baseline of 4. The description is sufficient in this regard.

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 (list) and resource (regions of Belarus with open procurement counts). It clearly distinguishes from siblings: get_tender fetches a single tender, search_tenders searches tenders, while this tool returns an aggregate regional view. No ambiguity.

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 usage is implied by the purpose: if you need regional aggregated counts, use this tool. However, there is no explicit statement of when to prefer this over search_tenders or get_tender, nor any exclusions or alternative conditions. The guidance is implicit rather than stated.

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