Enriquecer perfil de LinkedIn

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

The description discloses the async task_id return, which explains why readOnlyHint=false despite the 'obtains' framing — the call enqueues work rather than returning data inline, so this is not an annotation contradiction. It also names the payload fields (email, phone, professional data). It omits cost/credit implications and what happens on a failed lookup, which for an openWorldHint tool would be useful.

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?

Three short lines: what it returns, the input format, and the async handoff. Each sentence carries distinct, actionable information with no repetition of the title or schema.

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 one-parameter tool with an output schema, the description covers the three things an agent needs: the data it produces, the exact input format, and the required follow-up call to get_task_result. Nothing essential to a correct invocation 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 0% and the single parameter has no description, so the description must compensate — and it does by giving the exact accepted format: https://www.linkedin.com/in/<usuario>/. That is the most valuable piece of information for this tool. It doesn't state what happens for non-canonical URLs or whether company pages are accepted.

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?

States a specific verb and resource: it retrieves email, phone and professional data for ONE LinkedIn profile. The emphasized 'UN perfil' implicitly contrasts with the bulk/list enrichment siblings, though no sibling is named explicitly. An agent can still tell this is the single-profile lookup versus the bulk tools.

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?

Explains the async workflow: the call returns a task_id and the result must be collected with get_task_result, which is a genuine usage instruction that prevents the agent from expecting a direct payload. It does not explicitly say when to prefer this over start_bulk_enrichment or preview_list_enrichment, so the bulk/single split remains inferential.

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