get_company

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

No annotations are provided, so the description carries full burden. It mentions 'Returns cleaned data in TOON format' which adds some behavioral context about output formatting. However, it lacks critical details: whether this requires authentication, rate limits, what 'cleaned' means, if it's a read-only operation, or error conditions. For a tool with 4 parameters and no annotations, this is insufficient.

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 concise with two clear sentences. The first sentence states the core purpose, and the second adds important output format information. There's no wasted text. However, it could be slightly more structured by explicitly mentioning parameter relationships.

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 tool with 4 parameters, no annotations, and no output schema, the description is incomplete. It mentions the output format ('TOON format') which helps, but doesn't cover authentication needs, error handling, parameter interdependencies, or what happens when multiple identification parameters are provided. The agent would struggle to use this correctly without trial and error.

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 all 4 parameters thoroughly. The description adds no parameter-specific information beyond implying that parameters relate to identifying a company. It doesn't explain relationships between parameters (e.g., whether 'url', 'universalName', and 'search' are alternatives) or the purpose of 'save_dir'. Baseline 3 is appropriate when 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 tool's purpose: 'Get LinkedIn company information' specifies the verb ('Get') and resource ('LinkedIn company information'). It distinguishes from siblings like 'search_companies' by focusing on retrieval of specific company data rather than searching. However, it doesn't explicitly contrast with 'get_company_posts' which retrieves posts instead of company info.

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 use 'get_company' versus 'search_companies' (for finding companies) or 'get_company_posts' (for company posts). There are no prerequisites, exclusions, or context about which parameter combinations are valid.

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