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ZOOQ - LinkedIn Data for AI Agents

by io.github.baldiga

search_companies_live

Read-onlyIdempotent

LIVE company search. Its draw is hasJobs — an actively-hiring filter available nowhere else in the catalog — plus bucketed headcount search. For firmographic filtering (staff/follower counts, founded year, website) use search_companies instead. Offset-paginated. Not-found is free upstream. (Costs 10 Zooq credits.)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNoResults per page, 0-50 (default 25).
startNoPagination offset, 0-999.
hasJobsNoOnly companies with open postings — a hiring-intent signal. Accepted values: true, false.
keywordYesSearch keyword. Required by the upstream for this endpoint.
industryNoIndustry id(s), comma-separated. Takes an upstream id, NOT free text. No Zooq or upstream endpoint currently mints these ids, so free text is ignored (you get unfiltered results) — leave it unset until that changes. See ROADMAP F.
geoEntityIdNoHQ location filter. Geo entity id — this is LinkedIn's own public geo id, and it works. To find one: type your target city, state or country into the location box on LinkedIn search, pick the right match from the auto-complete dropdown, press enter to load the results page, then read `geoId=` followed by a long number out of the browser address bar (e.g. Israel = 101620260). Comma-separate for several. Resolve once and reuse it. Verified working on this endpoint. If you would rather filter by plain text, search_companies takes hq_city / hq_country_code instead.
headcountRangeNoEmployee-count bucket. Accepted values: 1-10, 11-50, 51-200, 201-500, 501-1000, 1001-5000, 5001-10000, 10001+.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already mark this as read-only, non-destructive, and open-world. The description adds valuable behavioral context beyond those: offset pagination, the 10 Zooq credit cost, and the not-found-free-upstream behavior. No contradictions 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.

Conciseness5/5

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

The description is compact and front-loaded. The first sentence establishes what the tool is, the second explains why it exists, and the remaining sentences cover routing, pagination, not-found behavior, and cost. Every sentence earns its place with no filler.

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

Completeness5/5

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

Given the rich output schema and annotations, the description covers all essential contextual needs: unique differentiators, sibling routing, pagination, cost, and not-found behavior. Nothing an agent needs to decide whether to call this tool is missing.

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

Parameters4/5

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

Schema description coverage is 100%, so the schema already documents all parameters. The description adds meaning beyond the schema by highlighting hasJobs as the unique differentiator and framing headcountRange as a bucketed search dimension, which helps an agent prioritize parameters.

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

Purpose5/5

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

The description states a specific verb and resource ('LIVE company search') and immediately identifies the tool's unique value: the hasJobs filter 'available nowhere else in the catalog' plus bucketed headcount search. It also explicitly names the sibling alternative (search_companies), making the tool easy to distinguish.

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

Usage Guidelines5/5

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

Usage guidance is explicit: it positions this tool as the one to use for hasJobs and headcount-bucket search, and directly routes firmographic filtering to search_companies instead. This covers when to use, when not to use, and names the alternative.

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

A3.7/5.0
Disambiguation3/5

Most tools are separated by domain prefixes and the descriptions are unusually explicit about differences, but there are direct overlaps: companies_name_lookup is the same upstream as search_companies, companies_entity_id vs companies_universal_name_to_id resolve different id spaces, and search_people/search_people_live plus search_companies/search_companies_live cover similar ground. An agent can usually pick correctly, but only after close reading.

Naming Consistency4/5

The set is consistently snake_case with readable domain prefixes like companies_, jobs_, posts_, profile_, and search_. Deviations include the unexplained g_* prefix, jobs_details_v2's version suffix, affiliate_program lacking a resource prefix, and the duplicate naming convention of companies_name_lookup vs search_companies.

Tool Count2/5

45 tools is well above the 25+ threshold and creates a heavy surface for an agent to scan. While the domains are broad, some tools are redundant (companies_name_lookup/search_companies) or tangential (affiliate_program), so the count is not fully justified.

Completeness4/5

The server covers people, companies, jobs, posts, email, schools, and skills with both search and detail endpoints, which is strong for a read-only LinkedIn API. Obvious gaps like a global post search or a company followers list are absent, but the existing paths support most workflows without dead ends.

Resources