Read LinkedIn Company Overview and About

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

Annotations already declare readOnly, idempotent, non-destructive. The description adds the specific behavior of 'Always captures exactly the Company overview and About page' and enumerates the precise fields captured, including 'exact field evidence.' This goes beyond annotations by telling the agent what to expect in the response.

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?

A single, information-dense sentence that leads with the primary action and resource, then lists captured fields. No redundant or filler content—every phrase contributes meaning. The structure is front-loaded and efficient.

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 description clearly defines the data scope and benefits from output schema and annotations. However, the lack of explanation for context_id and request_id makes it incomplete for invocation purposes, and there is no mention of error handling for non-visible companies. It's adequate but has 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?

Only 1 of 3 parameters (company_slug) has a description in the schema, and the tool description only explains the slug. The required context_id and request_id parameters are undocumented in both the schema and description, leaving agents without guidance on how to populate them. This is a significant gap given the low 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 uses the verb 'Read' with a specific resource 'LinkedIn Company' and clearly identifies the exact scope: by public slug, capturing the Company overview and About page. This distinguishes it from sibling search tools like linkedin.companies.search, making the purpose unmistakable.

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 clear context for when to use the tool: when you need a specific company's overview and About page using its public slug. It does not explicitly mention when not to use it or name alternatives, but the contrast with search tools is implied via 'exact' and 'slug'. Lack of explicit exclusion keeps it a step below perfect.

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