firmy_list

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

No annotations are provided, so the description carries the behavioral burden. It discloses that this is a read-only listing operation and specifies the kind of data returned (what companies do, AI-ready data). It does not discuss scale, pagination, or other behavior, but for a zero-parameter list tool the core behavior is clear.

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 short sentences with no waste; the main action and scope are front-loaded. The second sentence adds context but partially repeats the idea of 'data they expose to AI' with 'AI-ready data', so it is not perfectly tight.

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 lack of an output schema, the description conveys the general content of the response but leaves exact fields, structure, and any large-list behavior unspecified. For a simple zero-parameter catalog list this is adequate, though not deeply detailed.

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 input schema has zero parameters with 100% coverage, and the baseline for zero parameters is 4. The description adds relevant content expectations without needing to explain parameters that do not exist.

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 uses a specific verb ('List all') and a specific resource ('companies in the AiTop plástev business hive'), and clarifies the output focus: Czech businesses, their activities, and AI-ready data. This clearly distinguishes it from siblings like firmy_search and firmy_ask, which imply filtering and querying.

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 phrase 'List all companies' implies this tool is for retrieving the full catalog rather than searching or asking a question. However, the description does not explicitly name alternatives or state when not to use it, leaving some inference to the agent.

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