linkedin_get_profile

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

Annotations already declare the tool read-only, idempotent, and non-destructive. The description adds valuable behavioral context beyond annotations: it mentions a 5-minute cache (via the refresh parameter description) and that the tool reads the complete profile, giving the agent expectations about data freshness and scope. It doesn't mention rate limits or auth requirements, but with annotations already covering the safety profile, this is adequate.

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 two sentences long. The first sentence is dense with useful detail (listing all sections), and the second clearly states two specific use cases. Every clause carries meaning, no wasted words, and the most important information (what the tool reads) 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?

Given the tool has 4 optional parameters, a rich set of profile sections, and already strong annotations, the description covers the essential aspects: the full scope of data read, the two primary use cases, and evidence of the cache behavior. It doesn't describe return format or error cases, but with no output schema and read-only semantics, the description is sufficient for an agent to correctly invoke the tool for most profile-reading tasks.

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 schema already documents all four parameters. The description further enhances parameter understanding by clarifying the 'identifier' parameter values ('me', public identifier, URL, URN) and the 'refresh' parameter's cache-bypass behavior, which are not fully specified in the schema alone. However, the description doesn't elaborate on the exact format of the return value, which is fine given no output schema exists but the description could have added more context on response shape.

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 a specific verb ('Read a complete LinkedIn profile') and enumerates the exact sections included (headline, about, experience, education, etc.), making the tool's scope unmistakable. It also implicitly distinguishes this read tool from sibling mutation tools like linkedin_update_headline or linkedin_add_experience by framing it as the 'read' counterpart to those actions.

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 explicitly states when to use the tool: 'before writing any profile update' and 'before tailoring a resume.' It also offers clear context for recommended usage based on data freshness, implying the tool is the right choice whenever you need to review existing profile content before modifying it. While it doesn't name specific alternative tools, the context inherently distinguishes this read operation from the many profile-edit siblings.

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