Unipile: Linkedin List Job Applicants

List the applicants to one LinkedIn job posting.

Tool ID: unipile_linkedin_list_job_applicants

Run this action

Use the TypeScript SDK for one call. Use ctx.tools.execute(...) inside a Play for durable calls, scheduled calls, or CSV processing.

import { Deepline } from 'deepline';

const deepline = await Deepline.connect();
const result = await deepline.tools.execute(
  'unipile_linkedin_list_job_applicants',
  {
    "account_id": "123456789",
    "id": "id_123"
  },
);

console.log(result.toolResponse.raw);

CLI

deepline tools execute unipile_linkedin_list_job_applicants --input '{
  "account_id": "123456789",
  "id": "id_123"
}' --json

Example response

The static output schema lacks the details for a reliable example. Use deepline describe unipile_linkedin_list_job_applicants --json for the complete live contract.

Input reference

Retrieve all the users that have applied to a given offer.

Name	Type	Required	Default	Details
`payload.max_years_in_company`	`number`	No	—	Linkedin Recruiter native filter : YEARS IN CURRENT COMPANY.
`payload.min_years_in_company`	`number`	No	—	Linkedin Recruiter native filter : YEARS IN CURRENT COMPANY.
`payload.max_years_in_position`	`number`	No	—	Linkedin Recruiter native filter : YEARS IN CURRENT POSITION.
`payload.min_years_in_position`	`number`	No	—	Linkedin Recruiter native filter : YEARS IN CURRENT POSITION.
`payload.max_years_of_experience`	`number`	No	—	Linkedin Recruiter native filter : YEARS OF EXPERIENCE.
`payload.min_years_of_experience`	`number`	No	—	Linkedin Recruiter native filter : YEARS OF EXPERIENCE.
`payload.exclude_degree`	`array`	No	—	Linkedin Recruiter native filter : DEGREES (excluded).
`payload.include_degree`	`array`	No	—	Linkedin Recruiter native filter : DEGREES (included).
`payload.include_archived`	`boolean`	No	—	Whether the results should include archived applicants. Recruiter only.
`payload.ratings`	`string`	No	—	One or more ratings (UNRATED, GOOD_FIT, MAYBE, NOT_A_FIT) separated by commas. Classic only.
`payload.keywords`	`string`	No	—	Filter results with keywords.
`payload.sort_by`	`"relevance" \| "alphabetical" \| "newest_first" \| "screening_requirements"`	No	—	The sorting rule for applicants. Recruiter only. Allowed: `relevance`, `alphabetical`, `newest_first`, `screening_requirements`.
`payload.service`	`"CLASSIC" \| "RECRUITER"`	No	—	The Linkedin service the job posting depends on. Default is classic. Allowed: `CLASSIC`, `RECRUITER`.
`payload.limit`	`integer`	No	`10`	A limit for the number of items returned in the response. The value can be set between 1 and 100. Minimum: 1. Maximum: 100.
`payload.cursor`	`string`	No	—	A cursor for pagination purposes. To get the next page of entries, you need to make a new request and fulfill this field with the cursor received in the preceding request. This process should be repeated until all entries have been retrieved. Minimum length: 1.
`payload.account_id`	`string`	Yes	—	The ID of the account to trigger the request from.
`payload.id`	`string`	Yes	—	The ID of the job offer.

Output reference

Standard tool result payload.

Name	Type	Required	Default	Details
`result.data`	`object`	Yes	—	Provider response payload.
`result.data.object`	`"LinkedinJobApplicantList"`	Yes	—	Allowed: `LinkedinJobApplicantList`.
`result.data.job_posting_id`	`string`	Yes	—	A unique identifier. Minimum length: 1.
`result.data.items`	`array`	Yes	—	—
`result.data.items[].object`	`"LinkedinJobApplicant"`	Yes	—	Allowed: `LinkedinJobApplicant`.
`result.data.items[].id`	`string`	Yes	—	—
`result.data.items[].profile_id`	`string`	Yes	—	—
`result.data.items[].public_identifier`	`string`	Yes	—	—
`result.data.items[].public_profile_url`	`string`	Yes	—	—
`result.data.items[].name`	`string`	Yes	—	—
`result.data.items[].location`	`string`	Yes	—	—
`result.data.items[].headline`	`string`	Yes	—	—
`result.data.items[].profile_picture_url`	`string`	No	—	—
`result.data.items[].applied_at`	`number`	Yes	—	—
`result.data.items[].rating`	`"UNRATED" \| "GOOD_FIT" \| "MAYBE" \| "NOT_A_FIT"`	Yes	—	Allowed: `UNRATED`, `GOOD_FIT`, `MAYBE`, `NOT_A_FIT`.
`result.data.items[].hiring_state`	`string`	No	—	—
`result.data.items[].email_address`	`string`	No	—	—
`result.data.items[].phone_number`	`string`	No	—	—
`result.data.items[].contact_info`	`object`	No	—	—
`result.data.items[].contact_info.email_addresses`	`array`	Yes	—	—
`result.data.items[].contact_info.phone_numbers`	`array`	Yes	—	—
`result.data.items[].work_experience`	`array`	Yes	—	—
`result.data.items[].work_experience[].company`	`string \| null`	Yes	—	—
`result.data.items[].work_experience[].company_id`	`string`	No	—	—
`result.data.items[].work_experience[].position`	`string \| null`	Yes	—	—
`result.data.items[].work_experience[].location`	`string`	No	—	—
`result.data.items[].work_experience[].description`	`string`	No	—	—
`result.data.items[].work_experience[].picture_url`	`string`	No	—	—
`result.data.items[].work_experience[].start`	`object \| null`	Yes	—	—
`result.data.items[].work_experience[].start.year`	`number`	Yes	—	—
`result.data.items[].work_experience[].start.month`	`number`	Yes	—	—
`result.data.items[].work_experience[].end`	`object \| null`	Yes	—	—
`result.data.items[].work_experience[].end.year`	`number`	Yes	—	—
`result.data.items[].work_experience[].end.month`	`number`	Yes	—	—
`result.data.items[].education`	`array`	Yes	—	—
`result.data.items[].education[].school`	`string \| null`	Yes	—	—
`result.data.items[].education[].school_id`	`string`	No	—	—
`result.data.items[].education[].degree`	`string`	No	—	—
`result.data.items[].education[].description`	`string`	No	—	—
`result.data.items[].education[].field_of_study`	`string`	No	—	—
`result.data.items[].education[].picture_url`	`string`	No	—	—
`result.data.items[].education[].start`	`object \| null`	Yes	—	—
`result.data.items[].education[].start.year`	`number`	Yes	—	—
`result.data.items[].education[].start.month`	`number`	Yes	—	—
`result.data.items[].education[].end`	`object \| null`	Yes	—	—
`result.data.items[].education[].end.year`	`number`	Yes	—	—
`result.data.items[].education[].end.month`	`number`	Yes	—	—
`result.data.items[].screening_questions`	`array`	Yes	—	—
`result.data.items[].screening_questions[].question`	`string`	Yes	—	—
`result.data.items[].screening_questions[].answers`	`array`	Yes	—	—

The table shows the first 50 fields. Expand the raw schema below for every field.

Deepline cost

Pricing model: fixed (per call).
Estimated Deepline credits: 0 per pricing unit.
Provider-native pricing may still exist outside Deepline credit billing.

​Run this action

​CLI

​Example response

​Input reference

​Output reference

​Deepline cost

​Related documentation

Run this action

CLI

Example response

Input reference

Output reference

Deepline cost

Related documentation