get_tender_stats

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

With no annotations provided, the description carries the full burden. It discloses the nature of the output (counts, industries, countries) but does not explicitly state that the operation is read-only or describe any limitations like data freshness or access needs. It is enough to understand the behavior, but not richly detailed.

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 two sentences and immediately states the tool's purpose and data contents. It avoids any fluff or repetition, earning a top score for being concise and well-structured.

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?

Given the tool's simplicity (no parameters, no output schema), the description is complete. It covers what the tool returns (statistics), the scope (Canada + US), and when to use it (before searching). There are no missing details necessary for an agent to select and invoke 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?

The tool takes zero parameters, so there is no parameter semantics to clarify. The rubric assigns a baseline of 4 in this case, and the description appropriately focuses on the output rather than parameters.

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 starts with a specific verb and resource: 'Get current government tender statistics' and enumerates concrete data points (active tender count, covered industries, available countries). This clearly differentiates it from sibling tools like search_tenders and match_tenders, which focus on finding or matching tenders rather than summarizing dataset availability.

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 description explicitly tells the agent when to use this tool: 'Use this to check what data is available before searching.' This provides a clear workflow context, though it does not name alternative tools or describe when not to use it, so it falls short of full 5 criteria.

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