Scrape a LinkedIn profile

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

Even though the annotations already declare readOnlyHint and idempotentHint, the description adds substantial behavioral detail: it consumes no daily quota, only clicks the '…see more' expander, returns null/[] for hidden sections, and specifies the sole error condition (selector_not_found). It also clarifies connectionDegree semantics and result caps, going well beyond the annotations.

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 long but densely informative, with the core purpose and return fields front-loaded followed by parameter formats, behavioral notes, and edge cases. Every sentence adds operational value; no filler or tautology is present.

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?

With one optional parameter, strong annotations, no output schema, and no nested objects, this description covers all necessary invocation details: input formats, return fields, error behavior, and limits. An agent can correctly select and call this tool without needing additional documentation.

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?

The schema only defines profileUrl as a string with no description, giving 0% coverage. The description fully compensates by explaining all accepted input formats, the default when omitted, and what the tool reads from that URL. This gives an agent everything needed to pass the parameter correctly.

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 states a specific verb and resource: 'Reads a LinkedIn member profile and returns it as structured data,' and enumerates the exact fields returned. It is clearly distinguishable from sibling tools like linkedin_scrape_feed and linkedin_search_jobs, which target different data sources.

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 gives concrete usage context: accepted profileUrl formats (full URL, path, bare slug) and the behavior when omitted (reads the signed-in member's own profile). It does not explicitly name alternatives or when not to use this tool, but the profile-scoped purpose and sibling names make the choice reasonably clear.

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