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

Beyond the readOnly/idempotent/openWorld annotations, it discloses cost (10 credits per page), the single biggest behavioral risk, and explains the asymmetric boolean semantics of recently_changed_jobs and posted_on_linkedin, where False leaves the search unfiltered rather than excluding matches. It also documents list OR-ing, the 500-character keywords cap, and that company_linkedin_urls are resolved for the caller.

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 cost warning and the OR-semantics rule are front-loaded and the bulleted value sets are scannable. The only redundancy is mild editorializing ("the easiest tool to overspend with") in an otherwise dense, purposeful block.

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 19-parameter, zero-schema-documentation search tool, the description covers the highest-risk behaviors: pricing, pagination discipline, list semantics, boolean spotlight quirks, and the main filter value sets; an output schema exists, so return shape need not be described. It stops short of covering the remaining straightforward filters, which is the one gap keeping it off a 5.

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% across 19 parameters, so the description carries the full burden; it does add real meaning for keywords, company_name, company_linkedin_urls, company_ids, and both booleans, and enumerates valid value sets for four range/enum filters. However, parameters like school, function, industry, location, job_title, seniority, technology, profile_language, and page are left entirely unexplained, so compensation is partial.

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 opening sentence gives a specific verb and resource ("Find people") plus the intended semantic goal ("matching an ideal customer profile"), which immediately distinguishes this filtered-search tool from single-record siblings like get_person_profile. The subsequent filter paragraphs make the scope concrete enough that an agent knows what kind of query this tool answers.

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?

It states explicit when-to-use constraints: narrow filters before paginating, only request page 2 if page 1 genuinely failed to answer the question. It also routes the agent to the sibling list_filter_values to confirm valid value sets, so alternatives are named rather than implied.

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