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

Annotations already declare this as a safe read-only operation, so the description does not need to repeat that. It adds the behavioral detail that results are based on industry, tech stack, and target market, which is useful. However, it does not disclose potential quirks like pagination, error handling, or data source reliability, so only partial transparency beyond 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 extremely concise: two sentences, front-loaded with the primary purpose, and the second sentence adds essential detail without any fluff. Every word earns its place.

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?

The tool has no output schema, so the description should clarify what is returned. It says 'Returns similar companies' but does not describe the result fields, ranking, or default count. The parameter count is small and annotations cover safety, so this is adequate but not complete.

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?

With 0% schema description coverage, the description must carry the burden of parameter meaning. It explains that industry is one of the matching criteria, and company_name and limit are reasonably inferable from their names and defaults. Yet it does not clarify the exact role of the 'industry' parameter (e.g., as a filter vs. a hint) or how 'limit' behaves. This is partial compensation.

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 identifies the tool's function: finding competitors of a company. It specifies the verb ('find') and the resource ('competitors of a company'), and elaborates with the matching criteria (industry, tech stack, target market), which distinguishes it from broader search tools like 'search_companies' or 'company_intelligence'.

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: use when you need competitor companies. However, it does not explicitly state when to prefer this tool over alternatives such as 'search_companies' or 'company_intelligence', nor does it mention any exclusions or conditions. The context is clear but the guidance is not explicit.

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