Zooq

profile_employment_history

Read-onlyIdempotent

Complete LIVE work history for one person: per-role organization, title, description, location, parsed dates, per-role skills, and parallel-position groupings (concurrent titles kept distinct rather than flattened). Overlaps profile_full_experience, which reads the dataset record — use this when you need freshness, per-role skills, or correct handling of concurrent roles. Pass handle and Zooq resolves it at no extra credit cost, or pass entityId from profile_entity_id to skip the lookup. Not-found is free upstream. (Costs 10 Zooq credits.)

Input Schema

TableJSON Schema

Name	Required	Description	Default
`handle`	No	Public profile handle — the part after linkedin.com/in/ — or the full profile URL. Resolved to `entityId` automatically at no extra credit cost. Any person identifier is accepted here and sorted by format (handle, URL, ACoAA… entityId, prsn_ id). Provide `entityId` OR `handle`; `handle` is the simplest.
`entityId`	No	Live person entityId (ACoAA…) from profile_entity_id / profile_enrich; the urn:li:fsd_profile: form is accepted. A prsn_ id (dataset namespace, from profile_full) or a handle placed here is recognized and translated automatically. Provide `entityId` OR `handle`.

Output Schema

TableJSON Schema

Name	Required	Description	Default
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 the tool read-only, open-world, and idempotent, so the description's job is lighter, but it still adds valuable context: live freshness, a 10-Zooq-credit cost, no extra cost for handle resolution, and free upstream not-found behavior. This meaningfully informs agent decisions beyond the structured hints.

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?

Four sentences carry all the essential information with no filler, front-loading the core output and placing the alternative, cost, and lookup behavior after. Every clause contributes a distinct fact needed for selection or invocation.

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?

For a read-only lookup tool with an output schema and fully documented parameters, the description supplies the remaining operational context: freshness, concurrency handling, cost, not-found policy, and identifier resolution options. Nothing critical is missing for an agent to call this tool correctly.

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?

Parameter descriptions alone already cover 100% of the schema, so the baseline is 3. The description adds the operational tradeoff between handle and entityId — handle is auto-resolved at no extra cost while entityId skips the lookup — which aids correct invocation.

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?

States it returns complete live work history for one person and enumerates the specific per-role fields and the parallel-position grouping behavior. It also distinguishes itself from the overlapping dataset-record tool, so an agent can immediately tell what this tool uniquely provides.

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?

Explicitly says to use this tool when freshness, per-role skills, or correct concurrent-role handling are needed, and names profile_full_experience as the overlapping alternative that reads the dataset record. It also clarifies the choice between passing handle versus entityId based on whether the lookup should be skipped.

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.

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