> ## Documentation Index
> Fetch the complete documentation index at: https://docs.clarifeye.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# List assignable users

> List project members who can be assigned an interview (tech/contributor
profiles and pending tech/contributor invites), flagging admins. **Admin only.**




## OpenAPI

````yaml /api-reference/openapi-full.yaml get /projects/{project_id}/interviews/assignable-users/
openapi: 3.0.3
info:
  title: Clarifeye Platform API — Full API Documentation
  description: >
    Complete REST API reference for the Clarifeye Platform.


    Documents every endpoint exposed by the platform — the public surface plus

    the advanced surface: pipeline customization (extraction flows, pipeline

    runs, warehouse tables, document tag/metadata configuration), the pre-MCP

    AI surface (agent settings, playground conversations, conversation-scoped

    feedback views, notifications), and the impersonation header. New AI

    integrations should consume knowledge via MCP rather than the

    conversation/agent-settings endpoints documented here.


    ## Authentication

    All endpoints require authentication. Include the Authorization header in
    every request using either format:

    - `Authorization: Token <token_key>`

    - `Authorization: Bearer <token_key>`


    ## Organization API Key Authentication

    The user-provisioning endpoints authenticate with an **org-scoped API key**
    instead of a user token:

    - `Authorization: Api-Key <key>`


    The key is minted internally by Clarifeye (not self-service) and is scoped
    to a single

    organization — it can only act on the organization whose UUID matches the
    `{id}` in the

    request path. The email domains a key may pre-create accounts for are
    configured by

    Clarifeye on the organization (`allowed_provisioning_domains`). Once you
    have a key and

    your domains are set, call `POST /organizations/{id}/provision-user/` to
    pre-create users

    and `POST /organizations/{id}/deprovision-user/` to remove them.


    ## Impersonation


    Certain endpoints support user impersonation for creating or listing data on
    behalf of other users.

    This is useful for integrating external systems that need to attribute
    actions to specific users.


    **Header:** `X-Impersonate-Email`


    **Required Permission:** `CAN_IMPERSONATE_OTHER_USERS` (contact Clarifeye to
    enable this permission)


    **Behavior:**

    - If the header is provided and the impersonator has the required
    permission, the action is performed as the target user

    - If the target user is not found, the request proceeds as the original
    authenticated user

    - If the target user does not have access to the project, the request
    proceeds as the original authenticated user

    - If the impersonator lacks the `CAN_IMPERSONATE_OTHER_USERS` permission,
    the header is ignored
  version: 1.0.0
  contact:
    name: Clarifeye Support
servers:
  - url: https://eu.app.clarifeye.ai/api/v1
    description: EU
  - url: https://us.app.clarifeye.ai/api/v1
    description: US
security:
  - BearerAuth: []
  - TokenAuth: []
tags:
  - name: Users
    description: Manage users within a project
  - name: Invitations
    description: Manage project invitations
  - name: Documents
    description: Manage documents within a project
  - name: Agent Settings
    description: Manage AI agent configurations
  - name: Conversations
    description: Create and interact with AI-powered conversations
  - name: Interviews
    description: Assign and review structured interview conversations
  - name: Feedback
    description: >-
      Submit and review feedback — standalone (content-only), agent-submitted
      (MCP), or linked to a conversation message
  - name: Tools
    description: Execute configured AI tools with custom parameters
  - name: Tables
    description: Perform CRUD operations on warehouse tables
  - name: Notifications
    description: Manage project-scoped notifications for users
  - name: Extraction Flows
    description: >-
      Manage extraction flows (auto-sync DAGs) — list, run, inspect statistics,
      update, and publish
  - name: Object Extractors
    description: |
      Extract structured data (instances of a Pydantic model) from chunks or
      blocks of documents. Update auto-creates a new `ObjectExtractorVersion`
      when version-bearing fields change.
  - name: Tag Extractors
    description: |
      Apply hierarchical metadata tags to chunks or documents using an LLM.
      Update auto-creates a new `TagExtractorVersion` when version-bearing
      fields change.
  - name: Chunks Extractors
    description: |
      Segment parsed documents into chunks for downstream processing.
      Update auto-creates a new `ChunksExtractorVersion` when version-bearing
      fields change.
  - name: Parsing Extractors
    description: |
      Convert source documents to text blocks via the parsing pipeline.
      Update auto-creates a new `ParsingExtractorVersion` when version-bearing
      fields change.
  - name: Document Filter Extractors
    description: |
      Restrict a downstream pipeline branch to documents matching a filter.
      Update auto-creates a new version when the filter changes.
  - name: Chunk Tag Filter Extractors
    description: |
      Restrict a downstream pipeline branch to chunks carrying specific tags.
      Update auto-creates a new version when the filter changes.
  - name: Document Tag Extractors
    description: |
      Apply a flat set of metadata tags to each document. Update auto-creates
      a new version when version-bearing fields change.
  - name: Tag Alerts Extractors
    description: |
      Run LLM-based alerts over already-extracted tag rows. Update auto-creates
      a new version when version-bearing fields change.
  - name: Object Alerts Extractors
    description: >
      Run LLM-based alerts over already-extracted object rows. Update
      auto-creates

      a new version when version-bearing fields change.
  - name: Imported Object Extractors
    description: |
      Hold objects imported from an external system (rather than extracted by
      an LLM). Useful for hydrating the warehouse with data produced outside
      the platform.
  - name: Pipeline Runs
    description: >-
      Inspect pipeline runs queued by extraction flows or other pipeline
      triggers — list runs and fetch the details/status of a single run
  - name: User Provisioning
    description: >
      Pre-create and de-provision org users via an org-scoped API key

      (`Authorization: Api-Key <key>`). The organization is resolved from the
      key.
  - name: Organization API Keys
    description: >
      Superuser management of org-scoped provisioning API keys. Minting and
      revoking

      are superuser-only; org admins can list/retrieve/reveal their own org's
      keys.
  - name: Design System Templates
    description: Reference/example files attached to a design template.
paths:
  /projects/{project_id}/interviews/assignable-users/:
    get:
      tags:
        - Interviews
      summary: List assignable users
      description: >
        List project members who can be assigned an interview (tech/contributor

        profiles and pending tech/contributor invites), flagging admins. **Admin
        only.**
      operationId: listAssignableInterviewUsers
      parameters:
        - $ref: '#/components/parameters/ProjectId'
      responses:
        '200':
          description: Successful response
          content:
            application/json:
              schema:
                type: object
                properties:
                  users:
                    type: array
                    items:
                      type: object
                      properties:
                        id:
                          type: string
                          format: uuid
                          nullable: true
                          description: Member user id; null for a pending invite.
                        email:
                          type: string
                          format: email
                        is_admin:
                          type: boolean
                        pending_invite:
                          type: boolean
                          description: >-
                            True when this is a not-yet-accepted invite rather
                            than a joined member.
                  non_interviewable_emails:
                    type: array
                    description: >
                      Emails of members who exist but can't be interviewed (data
                      readers).

                      Out-of-process callers use this to refuse such recipients
                      up front

                      instead of failing the whole batch at send.
                    items:
                      type: string
                      format: email
        '401':
          $ref: '#/components/responses/Unauthorized'
        '403':
          $ref: '#/components/responses/Forbidden'
        '404':
          $ref: '#/components/responses/NotFound'
components:
  parameters:
    ProjectId:
      name: project_id
      in: path
      required: true
      description: UUID of the project
      schema:
        type: string
        format: uuid
  responses:
    Unauthorized:
      description: Unauthorized - missing or invalid authentication
      content:
        application/json:
          schema:
            $ref: '#/components/schemas/Error'
          example:
            error: Authentication credentials were not provided.
    Forbidden:
      description: Forbidden - insufficient permissions
      content:
        application/json:
          schema:
            $ref: '#/components/schemas/Error'
          example:
            error: You do not have permission to perform this action.
    NotFound:
      description: Not found - resource does not exist
      content:
        application/json:
          schema:
            $ref: '#/components/schemas/Error'
          example:
            error: Not found.
  schemas:
    Error:
      type: object
      properties:
        error:
          type: string
          description: Error message
      example:
        error: User not found
  securitySchemes:
    BearerAuth:
      type: http
      scheme: bearer
      description: 'Use Authorization: Bearer <token>'
    TokenAuth:
      type: apiKey
      in: header
      name: Authorization
      description: 'Use Authorization: Token <token>'

````