run_linkedin_company_employee

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

No annotations are supplied, so the description carries the entire burden, yet it discloses nothing about pagination (startPage/maxResults), rate limits, credential requirements, or the scraperMode behavior. 'People-style filters' hints at filter semantics but stops short of describing actual behavior.

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 front-loaded sentence with no filler. It is efficient, though its brevity is a symptom of under-specification rather than disciplined conciseness.

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 14-parameter search tool with no annotations, no output schema, and zero schema coverage, one sentence is far too thin. The agent has insufficient information to select filters or predict results.

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 14 parameters at 0% schema description coverage, the schema documents nothing. The description only gestures at 'people-style filters' without explaining any of companies, locations, seniorityLevelFilter, functionFilter, yearsOfExperienceFilter, etc., leaving nearly all parameters undefined for the agent.

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 names a specific verb (searches) and resource (LinkedIn employees for one or more companies), so the agent knows this returns employee records. It partially distinguishes itself from run_linkedin_people_search by scoping to companies, but never names or contrasts the sibling directly, so the differentiation is inferential rather than explicit.

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?

There is no when-to-use or when-not-to-use guidance and no named alternative among the many LinkedIn siblings (run_linkedin_people_search, run_linkedin_company_search). The agent must infer usage purely from the tool name.

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