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

With zero annotations, the description carries the full disclosure burden and does so thoroughly: it reveals the cost side effect (one profile view from the shared daily budget), the data-quality caveat that emails are UNVERIFIED pattern guesses with email_confidence=pattern_guess, and the scope of returned data. This is rich behavioral context for an agent deciding whether to invoke the tool.

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 sentences front-load the core behavior, then layer the email caveat and cost warning, with each clause carrying operational weight. The parenthetical 'same lookup the SDR hunters use' is mild color rather than hard information, keeping this just short of zero-waste.

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 single-parameter tool with no annotations or output schema, the description covers inputs (URL format), outputs (five fields plus optional unverified email), and operational impact (budget cost). It omits the prerequisite that a LinkedIn account must be connected (a gap given siblings connect_linkedin_account/list_linkedin_accounts) and any failure behavior when the budget is exhausted or the profile is not found.

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 lone linkedin_url parameter has no schema documentation, so the description must compensate — and it does by specifying the expected format (a linkedin.com/in/... URL). It stops short of stating validation/error behavior for malformed URLs, but the format constraint is the essential semantic for correct invocation.

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 ('Fetch') with a concrete resource (a linkedin.com/in/... URL) and enumerates the exact fields returned (name/title/current employer/avatar/location), making the tool's function unmistakable. It doesn't explicitly name a sibling to differentiate from, though the LinkedIn-URL input makes it inherently distinct from CRM and SDR siblings like sdr_get_person_detail or crm_get_lead.

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?

Provides clear operational context and an explicit exclusion: it costs one profile view from the shared daily LinkedIn budget and 'do not loop over big lists.' However, it never names an alternative tool for cases the agent might confuse (e.g., sdr_get_person_detail or crm_get_lead), so routing guidance is left to inference.

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