get_top_companies

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the tool retrieves data ('Get') and specifies metrics like 'enriched job count' and timeframes ('last 7d and 30d'), but it does not cover critical aspects such as whether this is a read-only operation, potential rate limits, authentication needs, or the format of returned data. For a tool with zero annotation coverage, this is a significant gap.

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, efficient sentence that front-loads the core purpose without any wasted words. It directly states what the tool does and includes key details like timeframes, making it highly 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 has 0 parameters and no output schema, the description adequately covers the purpose and output semantics. However, it lacks behavioral details (e.g., read-only nature, data format) and usage guidelines, which are important for a tool in a server with many siblings. This makes it minimally viable but with clear gaps.

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 0 parameters with 100% coverage, so no parameter documentation is needed. The description adds value by explaining the semantics of the output—'top companies by enriched job count, with recent activity'—which clarifies what the tool returns beyond the schema. This justifies a score above the baseline of 3 for high schema coverage.

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 clearly states the tool's purpose: 'Get top companies by enriched job count, with recent activity (last 7d and 30d).' It specifies the verb ('Get'), resource ('top companies'), and key metrics ('enriched job count' and 'recent activity'). However, it does not explicitly distinguish this from sibling tools like 'get_categories' or 'get_top_titles', which reduces the score from 5 to 4.

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 provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites, context, or exclusions, nor does it reference sibling tools like 'get_stats_overview' or 'get_title_trends' for comparison. This lack of usage context leaves the agent without clear direction.

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