> ## Documentation Index > Fetch the complete documentation index at: https://developer.jobmojito.com/llms.txt > Use this file to discover all available pages before exploring further. # Run pre-screening on a plaintext resume > Stores a plaintext candidate resume, runs AI pre-screening against the position definition, records the result and returns the AI recommendation and analysis. If the candidate is not in the pre-screening candidate_action state, an early `{ decision_status, message }` object is returned with HTTP 200. ## OpenAPI ````yaml https://cool.jobmojito.com/functions/v1/openapi post /job-interview-pre-screening-api-resume-text openapi: 3.1.0 info: title: JobMojito API version: 1.0.0 description: >- Public API for JobMojito, served by Supabase Edge Functions. Authenticate with a Supabase JWT access token via the Authorization header. servers: - url: https://cool.jobmojito.com/functions/v1 description: Production security: [] tags: - name: Interviews description: >- Create, configure and manage interview / coaching / assessment definitions. - name: Results description: >- Interview results, transcripts, reports, re-attempt requests and analytics. - name: Candidates description: List and manage candidates. - name: Knowledge base description: Upload documents used to generate knowledge-base interviews. - name: Resume & Form verification description: Pre-screen candidates from resumes and forms. - name: Admin description: >- Account administration — invite team/coaching users, manage sub-merchants and avatar templates. paths: /job-interview-pre-screening-api-resume-text: post: tags: - Resume & Form verification summary: Run pre-screening on a plaintext resume description: >- Stores a plaintext candidate resume, runs AI pre-screening against the position definition, records the result and returns the AI recommendation and analysis. If the candidate is not in the pre-screening candidate_action state, an early `{ decision_status, message }` object is returned with HTTP 200. requestBody: required: true content: application/json: schema: $ref: '#/components/schemas/PreScreeningResumeTextRequest' responses: '200': description: >- Pre-screening completed, or an early `{ decision_status, message }` result when the candidate is not in the pre-screening candidate_action state. content: application/json: schema: anyOf: - $ref: '#/components/schemas/PreScreeningResumeTextResponse' - $ref: '#/components/schemas/PreScreeningNotApplicable' '401': description: Missing or invalid authentication. content: application/json: schema: $ref: '#/components/schemas/Error' '403': description: Authenticated user is not a merchant user. content: application/json: schema: $ref: '#/components/schemas/Error' '404': description: Position not found or does not belong to this merchant. content: application/json: schema: $ref: '#/components/schemas/Error' '422': description: Validation error (missing required field or unresolved merchant_id). content: application/json: schema: $ref: '#/components/schemas/Error' '500': description: Server error. content: application/json: schema: $ref: '#/components/schemas/Error' security: - bearerAuth: [] components: schemas: PreScreeningResumeTextRequest: type: object properties: position_id: type: string minLength: 1 description: >- Position (position_def_set) id the candidate is being screened against. example: 00000000-0000-0000-0000-000000000000 candidate_name: type: string minLength: 1 description: Candidate full name. example: Jane Doe candidate_email: type: string minLength: 1 description: Candidate email (normalised to trimmed lowercase). example: jane.doe@example.com candidate_country_code: type: string minLength: 1 description: Candidate country code, used as default residency/nationality. example: US candidate_resume: type: string minLength: 1 description: Plaintext candidate resume. example: Experienced software engineer with 8 years ... candidate_external_id: type: string description: Optional external identifier stored on the candidate profile. example: ATS-12345 candidate_linkedin_url: type: string description: Optional LinkedIn profile URL stored on the candidate profile. example: https://www.linkedin.com/in/jane-doe form: type: object properties: education: type: string description: Highest education level key. example: masters_degree languages: type: array items: type: object properties: code: type: string description: Language code. example: en level: type: string description: Proficiency level key. example: c2 description: Candidate language proficiencies. residency: type: string description: >- Country code of residency. Defaults to candidate_country_code when omitted. example: US nationality: type: string description: >- Country code of nationality. Defaults to candidate_country_code when omitted. example: US visa: type: string description: Visa status key. example: has_visa age: type: integer description: Candidate age in years. example: 30 gender: type: string description: 'Candidate gender (free text; standard values: male, female).' example: male additionalProperties: nullable: true description: >- Optional structured pre-screening form used by the assessment rules. Custom fields (defined via form_fields) are also accepted. required: - position_id - candidate_name - candidate_email - candidate_country_code - candidate_resume PreScreeningResumeTextResponse: type: object properties: success: type: boolean example: true decision_status: type: string description: Applied decision status for the pre-screening step. example: recruiter_action recommendation: type: string enum: - ai_accept - ai_reject - recruiter_action description: AI recommendation derived from the pre-screening status. example: recruiter_action profile_interview_id: type: string description: Candidate profile_interview id. interview_result_pre_screening_id: type: string description: Inserted interview_result_pre_screening id. interview_file_id: type: string description: Stored resume interview_file id. pre_screening_score: type: number nullable: true description: AI match score. resume_ai_analysis: type: string nullable: true description: AI resume analysis feedback. resume_ai_education: type: string nullable: true description: AI-detected education level of the candidate. resume_ai_technical_experience: type: number nullable: true description: AI-estimated years of relevant experience. resume_ai_is_switching_profession: type: boolean nullable: true description: Whether the candidate is switching profession. processing_reason: type: string nullable: true description: Reason the candidate failed screening, when applicable. required: - success - decision_status - recommendation - profile_interview_id - interview_result_pre_screening_id - interview_file_id - pre_screening_score - resume_ai_analysis - resume_ai_education - resume_ai_technical_experience - resume_ai_is_switching_profession - processing_reason description: >- 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. PreScreeningNotApplicable: type: object properties: decision_status: type: string example: unknown message: type: string required: - decision_status - message Error: type: object properties: error: type: string example: Field is required. name: type: string example: interview_result_id required: - error securitySchemes: bearerAuth: type: http scheme: bearer bearerFormat: JWT description: 'Supabase JWT access token, passed as `Authorization: Bearer `.' ````