Zooq

search_people

Read-onlyIdempotent

Search professional records with rich filters — name, title, company, skills, education, tenure, geography. Cursor-paginated. (Costs 10 Zooq credits.)

Input Schema

TableJSON Schema

Name	Required	Description
`limit`	No	Results per page, 1-50 (default 20).
`title`	No	Job-title match (min 3 chars).
`cursor`	No	Opaque pagination cursor; omit for the first page.
`degree`	No	Degree filter.
`skills`	No	Comma-separated normalized skill names. Resolve via /g/title-skills-lookup.
`summary`	No	Free-text summary/about match (min 3 chars).
`geo_city`	No	City name (min 3 chars).
`headline`	No	Free-text headline match (min 3 chars).
`last_name`	No	Last name (min 3 chars).
`first_name`	No	First name (min 3 chars).
`is_creator`	No	Only content creators.
`is_premium`	No	Only premium members.
`current_only`	No	Restrict title/company matches to current positions.
`is_boomerang`	No	Only people who rejoined a former employer.
`skills_match`	No	Skill match mode. Accepted values: any (default), all.
`certifications`	No	Certification name filter.
`field_of_study`	No	Field-of-study filter.
`education_level`	No	Education level filter.
`institution_ids`	No	Comma-separated institution ids (inst_...). Resolve via /search/schools.
`skill_count_max`	No	Maximum number of listed skills.
`skill_count_min`	No	Minimum number of listed skills.
`speaks_language`	No	Spoken-language filter.
`geo_country_code`	No	ISO country code.
`last_change_type`	No	Job-change type. Accepted values: joined, left, title_change.
`primary_language`	No	Profile primary language code, e.g. en.
`tenure_max_years`	No	Maximum tenure in current role (years).
`tenure_min_years`	No	Minimum tenure in current role (years).
`company_count_max`	No	Maximum number of companies in history.
`company_count_min`	No	Minimum number of companies in history.
`organization_slugs`	No	Comma-separated company slugs — the part after linkedin.com/company/. Company URLs and org_ ids (from companies_info / search_companies) are accepted and translated. Combine with current_only=true for people who work there NOW.
`certification_authority`	No	Certification issuing authority filter.
`last_change_within_days`	No	Only people with a job change in the last N days.
`current_company_count_min`	No	Minimum number of concurrent current companies.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`items`	No	Array in the example

TDQS

A3.5/5.0

Behavior4/5

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

Annotations already establish read-only, open-world, idempotent, and non-destructive behavior. The description adds two meaningful behavioral facts not in the annotations: cursor-based pagination and a 10-credit cost, both of which help an agent decide whether and how to invoke it.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short sentences deliver the core search scope upfront, then tack on pagination and cost in a compact parenthetical. Every word earns its place, and there is no restating of the tool name or schema.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With 33 parameters fully documented in the schema and an output schema present, the description does not need to explain return values. However, it omits the dataset-versus-live distinction that separates this tool from the similarly named search_people_live, which is a notable gap in an otherwise well-covered context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so every parameter is already individually documented. The description's filter summary (name, title, company, skills, education, tenure, geography) offers only high-level categorization and adds no new constraints or relationships beyond the schema, so the baseline of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb and resource ('Search professional records') and enumerates the major filter dimensions, so an agent can tell this is a people-search tool. However, it does not differentiate this dataset-backed search from the sibling search_people_live, leaving some ambiguity about which 'search people' tool to choose.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives no guidance on when to use this tool versus alternatives such as search_people_live, search_alumni, or search_job_changes. It mentions cost and pagination but provides no conditions, exclusions, or alternative routing.

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

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TDQS

A3.6/5.0

Disambiguation2/5

Many tools have strongly overlapping purposes: companies_name_lookup is explicitly equivalent to search_companies, companies_enrich/companies_info/companies_universal_name_to_id all return company-profile data, and profile_full overlaps with profile_employment_history and profile_enrich. The descriptions are detailed, but an agent would still frequently have to choose between near-duplicate endpoints.

Naming Consistency4/5

Tool names mostly follow a predictable resource-prefixed snake_case pattern, such as companies_*, jobs_*, posts_*, profile_*, and search_*, which makes the set readable and groupable. Minor inconsistencies like jobs_details_v2, g_title_skills_lookup, and mixed noun suffixes (info/details/full/lookup) keep it from a perfect score.

Tool Count2/5

44 tools is well beyond the heavy 25+ band, and several tools appear to be different lookup modes or near-duplicates of the same underlying capability. The broad LinkedIn-style data domain explains much of the size, but the set still feels bloated rather than well-scoped.

Completeness4/5

The API covers the core read-only professional-data workflows well: people, companies, jobs, posts, comments, likes, email discovery/verification, schools, skills, and targeted searches. Minor gaps exist, such as some job filters being unusable and no direct exposure of certain profile alias endpoints, but agents can generally complete end-to-end workflows.

Resources

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