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

Annotations already declare readOnlyHint, idempotentHint, and openWorldHint. The description adds extra behavioral context beyond annotations: it uses SalesNav API when available for richer data, implying data richness may vary by source. This sets accurate expectations, though it does not cover error cases or rate limits.

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?

Two concise sentences: the first states the purpose and output content, the second explains input formats and the SalesNav API nuance. Every sentence earns its place, and the most important information is front-loaded.

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 an output schema present and annotations carrying the read-only safety profile, the description provides everything needed to invoke the tool correctly: what it returns, how to target a profile, and the variable-data nuance. Nothing critical is missing.

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 both parameters are already well documented in the schema. The description largely restates the linkedin_id_or_url param semantics (URL, vanity, SalesNav URL, member ID) and adds no new information about account_id or parameter behavior. Baseline 3 is appropriate.

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 a specific verb + resource ('Fetch a complete LinkedIn profile') and lists data fields (name, headline, company, experience, skills…), clearly distinguishing it from sibling scrapers like scrape_post and scrape_search that target different resource types. It also enumerates accepted identifier forms, leaving no ambiguity about what the tool operates on.

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 a clear use case (fetching a complete profile) and explains how to specify the target (URL, vanity name, member ID, SalesNav URL). It does not explicitly name alternative tools or exclusions, but the context is sufficient to decide when to use it.

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