> ## Documentation Index > Fetch the complete documentation index at: https://docs.fribl.co/llms.txt > Use this file to discover all available pages before exploring further. # Update a CV > Apply a partial (dimension-scoped) update to a CV. Submit any non-empty subset of the allowed dimensions — `information`, `experience`, `education`, `hard_skills`, `soft_skills` — and only those will be processed and persisted. Unspecified dimensions are left untouched. `content_language` is required on every patch (whether the body touches text or skills dimensions); it can also be supplied via the `Accept-Language` request header, which the API auto-forwards. The 200 response echoes the full merged CV entity (with `created_at` / `updated_at` populated from the local task row), so the caller does not need a follow-up `GET /cvs/{id}`. ## OpenAPI ````yaml /api-reference/openapi.json put /cvs/{id} openapi: 3.1.0 info: title: Fribl API description: >- The Fribl API enables intelligent talent matching powered by AI. Analyze CVs and job descriptions from text or file uploads, search and manage skills, match candidates to positions with configurable scoring weights, and source candidate profiles from external databases. All document processing is asynchronous — submit documents for analysis, poll for status, and retrieve structured results when ready. version: 1.0.0 contact: name: Fribl Support url: https://fribl.co servers: - url: https://api-service.fribl.co/api/v1 description: Production security: - apiKey: [] tags: - name: CVs description: >- Upload, analyze, retrieve, update, and delete candidate CVs. CVs can be submitted as raw text or as PDF file uploads. Processing is asynchronous — use the status endpoint to track progress. - name: Jobs description: >- Upload, analyze, retrieve, update, and delete job descriptions. Jobs can be submitted as raw text or as PDF file uploads. Processing is asynchronous — use the status endpoint to track progress. - name: Matching description: >- Match analyzed CVs against job descriptions using AI-powered scoring. Configure weights across experience, hard skills, soft skills, and education dimensions to tailor match results to your hiring priorities. - name: Sourcing description: >- Search for candidate profiles from external sources, retrieve cached search results, and ingest selected profiles into your Fribl workspace for matching. - name: Skills description: >- Search the Fribl skills taxonomy and retrieve available languages for skill translation. These endpoints are publicly accessible and do not require authentication. - name: Tokens description: >- Inspect your workspace's usage-based token balance, review the ledger of every charge and refund, and read the live per-action price list. Billable endpoints deduct tokens and return 402 when the balance is insufficient. Tokens are purchased and managed in the Fribl Console (https://console.fribl.co). paths: /cvs/{id}: put: tags: - CVs summary: Update a CV description: >- Apply a partial (dimension-scoped) update to a CV. Submit any non-empty subset of the allowed dimensions — `information`, `experience`, `education`, `hard_skills`, `soft_skills` — and only those will be processed and persisted. Unspecified dimensions are left untouched. `content_language` is required on every patch (whether the body touches text or skills dimensions); it can also be supplied via the `Accept-Language` request header, which the API auto-forwards. The 200 response echoes the full merged CV entity (with `created_at` / `updated_at` populated from the local task row), so the caller does not need a follow-up `GET /cvs/{id}`. operationId: updateCv parameters: - name: id in: path required: true description: Unique identifier of the CV to update. schema: type: string format: uuid requestBody: required: true content: application/json: schema: $ref: '#/components/schemas/CvUpdateBody' responses: '200': description: >- CV updated successfully. `data` contains the full merged CV entity (the patch applied on top of the existing record), with `created_at` and `updated_at` populated from the local task row. content: application/json: schema: type: object properties: message: type: string example: >- Successfully updated CV with ID: 550e8400-e29b-41d4-a716-446655440000 data: $ref: '#/components/schemas/CV' required: - message - data '400': description: >- Update validation failed. The response may include `detail.message` and `detail.invalid_skills`. content: application/json: examples: missingContentLanguage: value: detail: message: >- content_language is required and must be a valid ISO 639-1 language code. invalidSkills: value: detail: message: Update validation failed. invalid_skills: - id: not-a-real-skill-id field: hard_skills message: >- Skill does not exist in the canonical graph/taxonomy. '401': $ref: '#/components/responses/Unauthorized' '404': $ref: '#/components/responses/NotFound' '422': description: The submitted body does not match the expected CV update schema. content: application/json: example: detail: message: >- Payload does not match CandidateUpdate schema for entity_type=Candidate. schema: CandidateUpdate errors: - type: missing loc: - information - first_name msg: Field required components: schemas: CvUpdateBody: type: object description: >- Partial (dimension-scoped) update for a CV. Submit any non-empty subset of the allowed dimensions — `information`, `experience`, `education`, `hard_skills`, `soft_skills` — and only those will be processed and persisted. Unspecified dimensions are left untouched. `content_language` is required on every patch (text or skills dimensions); it can also be supplied via the `Accept-Language` request header, in which case the body field can be omitted. properties: content_language: type: string description: >- ISO 639-1 language code of the submitted update payload. Required on every patch unless the `Accept-Language` header is set — the API forwards that header automatically. Without either, the request is rejected with 400. information: $ref: '#/components/schemas/CvInformation' experience: type: array items: $ref: '#/components/schemas/CvExperience' description: Updated list of work experience entries. education: type: array items: $ref: '#/components/schemas/CvEducation' description: Updated list of education entries. hard_skills: type: array items: $ref: '#/components/schemas/Skill' description: >- Updated hard skills. Skill IDs must already exist in the canonical taxonomy. soft_skills: type: array items: $ref: '#/components/schemas/Skill' description: >- Updated soft skills. Skill IDs must already exist in the canonical taxonomy. anyOf: - required: - information - required: - experience - required: - education - required: - hard_skills - required: - soft_skills CV: type: object description: A fully analyzed CV with extracted structured data. properties: id: type: string format: uuid description: Unique identifier of the CV. information: $ref: '#/components/schemas/CvInformation' experience: type: array items: $ref: '#/components/schemas/CvExperience' description: List of work experience entries. education: type: array items: $ref: '#/components/schemas/CvEducation' description: List of education entries. skill_descriptions: type: array items: type: string description: Raw skill descriptions extracted from the CV text. source_language: type: string description: Original content language associated with this CV. hard_skills: type: array items: $ref: '#/components/schemas/Skill' description: Structured hard skills identified from the CV. soft_skills: type: array items: $ref: '#/components/schemas/Skill' description: Structured soft skills identified from the CV. created_at: type: string format: date-time description: Timestamp when the CV was created. example: '2024-01-01T00:00:00.000Z' updated_at: type: string format: date-time description: Timestamp when the CV was last updated. example: '2024-01-01T00:00:00.000Z' CvInformation: type: object description: Personal and contact information extracted from a CV. properties: first_name: type: string description: Candidate's first name. example: John last_name: type: string description: Candidate's last name. example: Doe email: type: array items: type: string format: email description: List of email addresses. example: - john@example.com phone: type: array items: type: string description: List of phone numbers. example: - '+31612345678' linkedin: type: - string - 'null' description: LinkedIn profile URL. example: https://linkedin.com/in/johndoe github: type: - string - 'null' description: GitHub profile URL. example: https://github.com/johndoe website: type: - string - 'null' description: Personal website URL. example: https://johndoe.com address: $ref: '#/components/schemas/Address' CvExperience: type: object description: A single work experience entry from a CV. properties: title: type: string description: Job title or role. example: Senior Software Engineer activity_sector: type: string description: Industry or sector of the employer. example: Technology description: type: string description: Description of responsibilities and achievements. example: Led development of microservices architecture duration: type: integer description: Duration of the role in months. example: 36 start_date: type: string description: Start date in YYYY-MM format. example: 2020-01 end_date: type: string description: End date in YYYY-MM format. May be empty if the role is current. example: 2023-01 CvEducation: type: object description: A single education entry from a CV. properties: degree: type: string description: Degree obtained or pursued. example: Master of Science major: type: string description: Field of study or major. example: Computer Science score: type: string description: Grade, GPA, or distinction achieved. example: Cum Laude institution_name: type: string description: Name of the educational institution. example: University of Amsterdam start_date: type: string description: Start date in YYYY-MM format. example: 2015-09 end_date: type: string description: End date in YYYY-MM format. example: 2017-06 Skill: type: object description: >- A skill identified from a CV or job description, with type classification and match relationship. properties: id: type: string format: uuid description: Unique identifier of the skill. skill: type: string description: Name of the skill. example: JavaScript type: type: string enum: - hard-skill - soft-skill description: >- Canonical English type enum for the skill. This field is not translated. relationship: type: string enum: - required - optional - satisfies description: >- Canonical English relationship enum for the associated CV or job. This field is not translated. explanation: type: - string - 'null' description: >- AI-generated explanation of how this skill was identified or evaluated. example: Candidate demonstrates strong JavaScript proficiency ErrorResponse: type: object description: Standard error response. properties: error: type: string description: Human-readable error message. required: - error Address: type: object description: A geographic address. properties: city: type: string description: City name. example: Amsterdam country: type: string description: Country name. example: Netherlands responses: Unauthorized: description: >- Authentication failed. Provide a valid API key in the `x-api-key` header. content: application/json: schema: $ref: '#/components/schemas/ErrorResponse' NotFound: description: The requested resource was not found. content: application/json: schema: $ref: '#/components/schemas/ErrorResponse' securitySchemes: apiKey: type: apiKey in: header name: x-api-key description: >- API key in UUID format. Include this header with every authenticated request. ````