Resolve LinkedIn URL

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

Annotations already provide readOnlyHint=true and idempotentHint=true. The description adds value by specifying that the output is a flat Clay-ready JSON row and that it consumes Apify credits per call. No contradiction with annotations.

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, front-loaded with the main purpose, and each sentence adds necessary information without redundancy. Highly efficient.

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?

Despite lacking an output schema, the description enumerates the key outputs (confidence score, firmographics, social links) and describes the format (flat Clay-ready JSON row). It also notes prerequisites and cost, covering all relevant context for a parameter-light tool.

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 100%, and the description paraphrases the schema by restating the at-least-one requirement. It adds a minor example for company_domain (e.g., stripe.com), but does not significantly enhance understanding beyond what the schema provides.

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 uses a specific verb ('resolve') and clearly identifies the resource (company domain/name to LinkedIn URL) and output (confidence score, firmographics, social links as flat JSON row). It distinguishes from sibling tools which focus on aggregation, tech stack, or hiring signals.

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 the requirement to provide at least one of company_domain or company_name, and notes that it is read-only, requires an APIFY_TOKEN, and consumes Apify credits. This provides clear context for when to use the tool, though it does not directly compare with siblings.

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