Company Team & Decision-Maker Finder: Names, Titles, Emails

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

Annotations already declare readOnly, openWorld and non-destructive, but the description adds material behavior the annotations cannot convey: the tool runs a specific Apify Actor on the caller's own account, costs $0.002 per person found, does not charge for runs that find nobody, and is capped per call by run_max_charge_usd. It also discloses the return formats (Excel and CSV), which is essential for an agent that later needs to consume output.

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 output fields and source constraint are front-loaded in the first sentence, with operational and pricing details in the second paragraph. Two short paragraphs with no filler. Slightly dense packing of output fields into one sentence keeps it from a 5.

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 ten-parameter, zero-required tool with no output schema, the description supplies exactly what is missing: the shape of the results (person attributes plus email pattern and file formats), the sourcing rule, and the billing model. Combined with the fully documented schema and readOnly annotations, an agent has enough to call it correctly and predict the outcome.

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 100%, so every one of the ten parameters is already documented in the schema, including defaults, ranges and the PANDA_* environment fallbacks. The description only reinforces the cost semantics of run_max_charge_usd, which the schema already states. Baseline 3 applies because the description adds little parameter meaning beyond the schema.

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 and resource: find the people behind a company, sourced from its own team, leadership and staff pages, returning names, titles, seniority, department, emails, LinkedIn links and the email pattern. It also rules out a competing source ('No LinkedIn scraping'), which separates it from LinkedIn-based people search. It never names a sibling tool such as company_website_enricher or local_business_leads, so the differentiation is implicit rather than explicit.

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 opening 'Use this to find...' establishes the primary use case, and 'No LinkedIn scraping' plus 'from its own website' imply a source constraint. However, there is no when-not guidance, no prerequisites (other than the pricing/account note), and no named alternative for the case where a company has no team page or the agent needs LinkedIn-sourced contacts.

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