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

# List the caller's feature refinements

> Returns a paginated list of the authenticated user's own feature refinements, newest first.



## OpenAPI

````yaml api-reference/openapi.yaml GET /api/v1/feature-refinery
openapi: 3.0.1
info:
  title: MathFi.ai API
  description: >
    The MathFi.ai REST API runs the two products end to end.


    **Feature Refinery** takes your labelled data and works out which columns

    actually carry the signal. It returns a reduced train and test pair, a

    per-column keep/remove decision, and the performance target the refined data

    reached.


    **Model Crucible** takes a dataset, trains every algorithm family against it

    at once, ranks the results on held-out data by fewest wrong decisions, and

    keeps the best three as versions of one model. You pick which one
    predictions

    run against.


    Everything is asynchronous: you create a thing, upload to a signed URL,
    start

    it, then poll until the state is terminal. Nothing streams and nothing
    blocks.
  contact:
    name: MathFi.ai
    url: https://mathfi.ai
    email: support@mathfi.ai
  license:
    name: MathFi.ai
    url: https://mathfi.ai
  version: 1.0.0
servers:
  - url: https://{tenant}-api.mathfi.ai
    description: >-
      Your tenant's API. Each customer has their own, so the host varies.
      Replace {tenant} with the name issued when your tenant was created.
    variables:
      tenant:
        default: your-tenant
        description: The tenant name issued to you.
security:
  - BearerAuth: []
tags:
  - name: Authentication
    description: Exchange credentials for a bearer token
  - name: Feature Refinery
    description: Reduce a dataset to the columns that earn their place
  - name: Datasets
    description: >-
      Prepare labelled data for training, from uploads or from a finished
      refinement
  - name: Training
    description: Run the Crucible against a dataset and choose the champion model
  - name: Models
    description: Trained models and their versions
  - name: Predictions
    description: Score unlabelled data against a champion model
paths:
  /api/v1/feature-refinery:
    get:
      tags:
        - Feature Refinery
      summary: List the caller's feature refinements
      description: >-
        Returns a paginated list of the authenticated user's own feature
        refinements, newest first.
      operationId: listFeatureRefinements
      parameters:
        - name: offset
          in: query
          description: Number of elements to skip before starting to collect the result
          required: true
          schema:
            minimum: 0
            maximum: 1000000
            type: integer
            format: int64
        - name: limit
          in: query
          description: Maximum number of items to return
          required: true
          schema:
            minimum: 1
            maximum: 100
            type: integer
            format: int64
      responses:
        '200':
          description: Feature refinements successfully listed
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/FeatureRefineryList'
        '400':
          description: Invalid pagination parameters
        '500':
          description: Internal server error
components:
  schemas:
    FeatureRefineryList:
      required:
        - refinements
        - offset
        - limit
        - total
      type: object
      properties:
        refinements:
          type: array
          items:
            $ref: '#/components/schemas/FeatureRefineryListItem'
        offset:
          type: integer
          format: int64
        limit:
          type: integer
          format: int64
        total:
          type: integer
          format: int64
    FeatureRefineryListItem:
      description: >-
        One of the caller's runs, with its identity, state and the keys needed
        to follow it to progress and result.
      required:
        - featureRefinementKey
        - name
        - state
      type: object
      properties:
        featureRefinementKey:
          type: string
          format: uuid
        name:
          type: string
        trainFileName:
          type: string
          nullable: true
          description: >-
            Original filename of the training CSV, if supplied at create — helps
            identify the source dataset.
        state:
          type: string
        numberOfBuckets:
          type: integer
        createdOn:
          type: string
          description: ISO-8601 UTC instant the run was created.
        elapsedSeconds:
          type: integer
          format: int64
          description: >-
            Seconds the run has been processing (0 while pending; frozen once
            terminal).
        cancelRequested:
          type: boolean
          nullable: true
          description: >-
            True once a cancel has been requested for this run, and it stays set
            — it is NOT cleared when the run reaches its terminal CANCELLED
            state, so a cancelled run keeps cancelRequested=true. It is
            therefore safe to rely on after a restart, rather than remembering
            the request locally. Treat it as meaningful only while the state is
            non-terminal; once terminal, state is authoritative. Omitted (null)
            when no cancel was ever requested.
  securitySchemes:
    BearerAuth:
      type: http
      scheme: bearer
      bearerFormat: JWT

````