get_linkedin_company

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states it 'gets' information, implying a read-only operation, but doesn't mention potential side effects, authentication requirements, rate limits, error conditions, or what format the detailed information returns. This leaves significant gaps for an AI agent to understand how to invoke it safely and effectively.

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. There's zero waste—every word contributes to stating what the tool does. It's appropriately sized for a simple lookup tool.

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 no annotations and no output schema, the description is incomplete for a tool that presumably returns complex company data. It doesn't explain what 'detailed information' entails, potential authentication needs, or error handling. For a LinkedIn API tool with likely rich output, this leaves the agent under-informed about how to interpret results or handle failures.

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%, so the schema already documents both parameters ('company' and 'timeout') thoroughly. The description adds no additional meaning beyond what's in the schema—it doesn't explain what 'detailed information' includes or how parameters affect the output. Baseline 3 is appropriate when the schema does the heavy lifting.

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 verb 'Get' and the resource 'detailed information about a LinkedIn company', making the purpose unambiguous. It distinguishes from siblings like 'get_linkedin_company_employees' (which focuses on employees) or 'get_linkedin_profile' (which focuses on individual profiles). However, it doesn't specify what 'detailed information' includes, leaving some ambiguity.

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 doesn't mention when to choose this over 'get_linkedin_google_company' or 'search_linkedin_posts', nor does it specify prerequisites like needing authentication or valid company identifiers. Usage is implied only by the tool name.

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