Run pre-screening on a plaintext resume - JobMojito Developer / Agent

curl --request POST \ --url https://cool.jobmojito.com/functions/v1/job-interview-pre-screening-api-resume-text \ --header 'Authorization: Bearer <token>' \ --header 'Content-Type: application/json' \ --data ' { "position_id": "00000000-0000-0000-0000-000000000000", "candidate_name": "Jane Doe", "candidate_email": "jane.doe@example.com", "candidate_country_code": "US", "candidate_resume": "Experienced software engineer with 8 years ...", "candidate_external_id": "ATS-12345", "candidate_linkedin_url": "https://www.linkedin.com/in/jane-doe", "form": { "education": "masters_degree", "languages": [ { "code": "en", "level": "c2" } ], "residency": "US", "nationality": "US", "visa": "has_visa", "age": 30, "gender": "male" } } '

{ "success": true, "decision_status": "recruiter_action", "recommendation": "recruiter_action", "profile_interview_id": "<string>", "interview_result_pre_screening_id": "<string>", "interview_file_id": "<string>", "pre_screening_score": 123, "resume_ai_analysis": "<string>", "resume_ai_education": "<string>", "resume_ai_technical_experience": 123, "resume_ai_is_switching_profession": true, "processing_reason": "<string>" }

Authorizations

Authorization

string

header

required

Supabase JWT access token, passed as Authorization: Bearer <token>.

Body

application/json

position_id

string

required

Position (position_def_set) id the candidate is being screened against.

Minimum string length: 1

Example:

"00000000-0000-0000-0000-000000000000"

candidate_name

string

required

Candidate full name.

Minimum string length: 1

Example:

"Jane Doe"

candidate_email

string

required

Candidate email (normalised to trimmed lowercase).

Minimum string length: 1

Example:

"jane.doe@example.com"

candidate_country_code

string

required

Candidate country code, used as default residency/nationality.

Minimum string length: 1

Example:

"US"

candidate_resume

string

required

Plaintext candidate resume.

Minimum string length: 1

Example:

"Experienced software engineer with 8 years ..."

candidate_external_id

string

Optional external identifier stored on the candidate profile.

Example:

"ATS-12345"

candidate_linkedin_url

string

Optional LinkedIn profile URL stored on the candidate profile.

Example:

"https://www.linkedin.com/in/jane-doe"

form

object

Optional structured pre-screening form used by the assessment rules. Custom fields (defined via form_fields) are also accepted.

Show child attributes

Response

Pre-screening completed, or an early { decision_status, message } result when the candidate is not in the pre-screening candidate_action state.

Option 1
Option 2

Result of the pre-screening analysis. When the candidate is not in the pre-screening candidate_action state, a { decision_status, message } object is returned instead.

success

boolean

required

Example:

true

decision_status

string

required

Applied decision status for the pre-screening step.

Example:

"recruiter_action"

recommendation

enum<string>

required

AI recommendation derived from the pre-screening status.

Available options:

ai_accept,

ai_reject,

recruiter_action

Example:

"recruiter_action"

profile_interview_id

string

required

Candidate profile_interview id.

interview_result_pre_screening_id

string

required

Inserted interview_result_pre_screening id.

interview_file_id

string

required

Stored resume interview_file id.

pre_screening_score

number | null

required

AI match score.

resume_ai_analysis

string | null

required

AI resume analysis feedback.

resume_ai_education

string | null

required

AI-detected education level of the candidate.

resume_ai_technical_experience

number | null

required

AI-estimated years of relevant experience.

resume_ai_is_switching_profession

boolean | null

required

Whether the candidate is switching profession.

processing_reason

string | null

required

Reason the candidate failed screening, when applicable.