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

With no annotations, the description carries the full behavioral burden. It discloses that it returns open questions and rules against inventing data, and gives a clear rule set, but it does not cover permissions, side effects, idempotency, or response format, leaving key behavioral aspects unspecified.

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 sentences, front-loaded with the tool's purpose, followed by a clearly marked 'RULES:' section. No wasted words, though the second sentence could be tightened.

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 simple tool with no output schema, the description explains the return values (open questions, rules) but does not clarify what the 'overview' actually contains or how the registers are used. It is adequate but leaves gaps for an agent to fully understand the tool's scope.

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% (one optional 'query' param fully documented in the schema). The description adds no additional meaning about the parameter, so the baseline score of 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?

The description states a specific verb ('Get an overview') and a resource ('Croatian company registry due diligence workflows and data availability'), but the resource is meta and the tool name 'get_company_overview' suggests company data rather than workflow guidance, creating ambiguity. It does distinguish itself from data-fetching siblings by focusing on workflows and rules, but not 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 includes a process directive ('Interview the user first') but provides no explicit guidance on when to use this tool versus the many sibling tools (e.g., search_companies, get_company_by_id) or any exclusions. Usage is implied but not clearly stated.

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