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

Annotations already provide idempotentHint=true and destructiveHint=false, and the description adds meaningful behavioral detail beyond that: each result is validated, deduped by profile slug, invalid profile URLs are skipped, and errors are reported. This gives an agent a realistic model of what happens during execution. It stops short of describing error format or pipeline timing, but the added context is valuable.

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 compact and front-loaded with the primary action. Every sentence adds information: the purpose, the validation/dedup behavior, the handling of invalid URLs, the expected source of results, and the platform default. There is no filler or redundant restatement of the tool name.

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 tool with no output schema and an array input with multiple nested fields, the description covers the operational behavior and expected input source but omits return/response semantics beyond 'errors reported' and does not clarify the meaning of the four required identifier parameters. It is adequate for basic invocation but incomplete for fully confident use.

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%, so the description must compensate for the missing parameter documentation, but it only addresses 'platform' (defaults to 'linkedin') and broadly hints that 'results' should come from LinkedIn search extraction. The required identifiers workspaceId, campaignId, and accountId are left unexplained, and the individual fields inside each result object are not semantically clarified beyond their names.

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 clearly states the action ('Queue leads for enrichment') and the resource (leads), and adds meaningful specifics: validation, deduping by profile slug, and adding to the enrichment pipeline. It does not explicitly name or distinguish itself from sibling tools like add_leads_to_list or priority_enrich, but the enrichment-pipeline wording makes the core purpose unambiguous.

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 gives useful context about when the tool is appropriate: results should come from LinkedIn search page extraction, and platform defaults to 'linkedin'. However, it does not explain when to prefer this over related alternatives such as add_leads_to_list, import_leads_csv, or enrich_lead_contact_info, nor does it state any exclusions or prerequisites.

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