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Pre-screening scores a candidate’s résumé (and optional form answers) against a position, returning an AI recommendation. It’s two steps: define the pre-screening position, then submit candidates.
StepEndpointMCP tool
Create/update a pre-screening positionPOST /pre-screening-createupsert_pre_screening
Screen a candidate (plain text résumé)POST /job-interview-pre-screening-api-resume-textpre_screen_resume_text
Screen a candidate (uploaded file)POST /job-interview-pre-screening-api-resume-binarypre_screen_resume_binary

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1. Create the pre-screening position

curl -X POST https://cool.jobmojito.com/functions/v1/pre-screening-create \
  -H "Authorization: Bearer $SUPABASE_JWT" \
  -H "Content-Type: application/json" \
  -d '{
    "position_name": "Senior Backend Engineer",
    "position_location": "Remote (EU)",
    "position_country_code": "DE",
    "mojito_language_code": "en",
    "type": "resume",
    "status": "active",
    "position_description": "Backend role: Python, async APIs, AWS.",
    "candidate_expectations": "5+ yrs Python, cloud, SQL."
  }'
When creating, position_name, position_location, position_country_code, and mojito_language_code are required. type is resume, form, or resume_with_form. To update an existing position, pass update_position_def_set_id instead and only the fields you want to change. The response returns position_def_set_id (use it to screen candidates) and interview_pre_screening_id.

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2. Screen a candidate

Submit the candidate against the position_id (the position_def_set_id from step 1). Required: position_id, candidate_name, candidate_email, candidate_country_code, candidate_resume. 
curl -X POST https://cool.jobmojito.com/functions/v1/job-interview-pre-screening-api-resume-text \
  -H "Authorization: Bearer $SUPABASE_JWT" \
  -H "Content-Type: application/json" \
  -d '{
    "position_id": "POSITION_DEF_SET_UUID",
    "candidate_name": "Peter Parker",
    "candidate_email": "peter@parker.com",
    "candidate_country_code": "US",
    "candidate_resume": "Full plaintext résumé here…",
    "candidate_linkedin_url": "https://linkedin.com/in/peterparker",
    "form": {
      "education": "masters",
      "languages": [{ "code": "en", "level": "native" }],
      "residency": "US"
    }
  }'
For a binary file (PDF/DOCX), use job-interview-pre-screening-api-resume-binary with the same identity fields and the file payload instead of candidate_resume.

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Reading the result

A completed screen returns:
If the candidate isn’t in a screenable state, you’ll still get HTTP 200 with a short { "decision_status": …, "message": … } payload instead of a full result.

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Shortcut: pre-screen + interview in one call

To screen a candidate and get a ready interview link back in a single request, use POST /job-interview-create-for-candidate-with-token (create_interview_for_candidate). It resolves the position, runs pre-screening, and returns a tokenised interview_url plus a status like ai_accept or recruiter_action.

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Next steps

Invite candidates

Invite the candidates who passed screening.

Review results

Filter results by the pre-screening step to see screening outcomes.