linkedin_who_viewed_me

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

With no annotations provided, the description takes full responsibility for behavior. It discloses that some viewers appear as anonymous with limited info, states the server makes no attempt to identify them and fetches nothing about viewers, mentions the data source (Premium analytics page), and explains the redirect behavior and resulting pages_loaded count. This is exceptionally transparent.

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 longer than average, but it is front-loaded with the core purpose and organized into informative paragraphs. Each segment adds value: the high-intent context, anonymous viewer behavior, technical data source, and the redirect edge case. It is structured logically and avoids redundancy, though it could be tightened without losing clarity.

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 the tool's simplicity (one parameter, no nested objects) and the presence of an output schema, the description still covers all essential behavioral context: the kind of rows returned (name, headline, when, link), anonymous flagging, the data source, and the redirect quirk. It even explains what the server does not do. This is complete for an agent to use correctly.

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 baseline is 3. The sole parameter 'limit' is already fully described in the schema with default and max values; the tool description adds no additional semantic meaning or usage nuance beyond that. Thus it meets the baseline without needing extra explanation.

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 opens with 'List the people who viewed your profile, most recent first' — a precise verb and resource. It clearly distinguishes from sibling tools like linkedin_search_jobs or linkedin_my_applications by specifying the unique action of listing profile viewers, and provides additional context about the 'highest-intent signal in a job search.'

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 strong contextual guidance on when this tool is valuable ('the highest-intent signal in a job search' and notes that anonymous viewers are often the most useful part), implying usage in recruiter outreach scenarios. However, it does not explicitly exclude or compare against sibling tools, so it falls short of a 5 but is above a 3 due to the clear situational context.

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