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

With no annotations, the description carries the full burden and does so: it discloses the per-person cost against a daily budget, the background-job threshold (>3 handles, up to 50, returns job_id readable via get_job, user emailed on completion), and that opening the profile is what reveals the is_hiring / is_open_to_work badges. It also documents the return payload shape, none of which is in structured fields.

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?

Well front-loaded: purpose first, then the three-tool ordering, then constraints, cost, and return shape. Some repetition creeps in — the find_prospects comparison and the badge/touch cost point are restated in the final paragraph — but the length is largely justified by the volume of decision-relevant information.

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 9-parameter tool with 0% schema coverage, no annotations, and no output schema, the description supplies everything needed: input constraints, cost model, async behavior, and the concrete response shape including the fields each result carries. Nothing an agent needs to call it correctly or interpret results 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 coverage is 0% across 9 parameters, so the description must compensate, and it largely does: it states the at-least-one-of constraint across name/linkedin_id/iridium_handle/linkedin_ids/iridium_handles, expresses a preference ordering ('Prefer iridium_handle(s)'), and explains that name plus the hint fields is a keyword search opening up to 5 profiles. It does not explain the format expected for linkedin_id versus iridium_handle, which is the remaining gap.

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 ('Read the full LinkedIn profile(s)') with scope clarification ('people you already know, or several at once'). It explicitly contrasts itself against the two sibling tools find_person and find_prospects in a labelled ordering block, so an agent can distinguish the tools without opening schemas.

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?

Gives an explicit numbered workflow with when-to-use conditions ('Call it only when find_person's headline and proof are not enough') and when-not conditions ('to resolve a name, use find_person'; 'to find people you cannot yet name, use find_prospects'). It also names the alternative path for existing conversations (search_chats + schedule_manual_dm) and warns against messaging from a name alone.

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