---
title: "Api Evaluators List List"
method: GET
path: "/api/evaluators/list/"
tags: ["evaluations"]
---

# Api Evaluators List List

`GET /api/evaluators/list/`

List evaluators for an organization.

Superadmin: Can see all evaluators across all organizations.
Regular users: Can only see evaluators in their organization, plus PUBLIC
    (Respan-managed) evaluators when ``is_including_public_evaluators`` is
    truthy. Public evaluators are hidden by default for back-compat.

## Query parameters

- `page` integer
- `page_size` integer

## Headers

- `Authorization` string, required

## Response `200`

- PaginatedPublicEvaluatorListList
  - `count` integer, required
  - `next` string, uri, nullable
  - `previous` string, uri, nullable
  - `total_count` integer
  - `current_filters` FilterParamDictPydantic — Pydantic model for FilterParamDict. A dictionary that maps metric names to their filter parameters. Each key is a metric name (str), and each value can be: - A single MetricFilterParamPydantic (one condition) - A List[MetricFilterParamPydantic] (multiple conditions for same metric) - A FilterBundlePydantic (nested filter bundle with connector) Note: Uses extra="allow" for dynamic metric name fields. The __pydantic_extra__ annotation tells Pydantic what types to expect for extra fields, and generates typed additionalProperties in JSON Schema.
  - `filters_data` PaginatedPublicEvaluatorListListFiltersData
  - `results` PublicEvaluatorList[], required
    - `version_id` string
    - `configurations` object
    - `categorical_choices` object[], required
    - `score_config` object
    - `passing_conditions` object, nullable
    - `llm_config` object, nullable
    - `code_config` object, nullable
    - `project` string, nullable
    - `is_public` boolean, required
    - `created_by` Editor, required
      - `id` integer, required
      - `email` string, required
      - `name` string, required
      - `username` string
      - `first_name` string
      - `last_name` string
    - `updated_by` Editor, required
      - `id` integer, required
      - `email` string, required
      - `name` string, required
      - `username` string
      - `first_name` string
      - `last_name` string
    - `editor` Editor, required
      - `id` integer, required
      - `email` string, required
      - `name` string, required
      - `username` string
      - `first_name` string
      - `last_name` string
    - `tags` GenericTagDisplay[], required
      - `id` string, required
      - `name` string, required
      - `color` string, required
      - `created_at` string, date-time, required
      - `updated_at` string, date-time, required
    - `version_count` integer, required — Number of versions for this evaluator. Reads the ``version_count`` annotation added by the list querysets (see ``annotate_evaluator_version_count``). Falls back to 0 when the queryset was not annotated, so the serializer never issues a per-row count query.
    - `id` string
    - `version` integer
    - `is_read_only` boolean
    - `version_description` string
    - `evaluator_slug` string
    - `name` string, required
    - `description` string
    - `created_at` string, date-time, required
    - `updated_at` string, date-time, required
    - `type` 'llm' | 'code' | 'human' | 'function' | 'human_numerical' | 'human_categorical' | 'human_boolean' | 'human_text' | 'custom' — * `llm` - Llm * `code` - Code * `human` - Human * `function` - Function * `human_numerical` - Human Numerical * `human_categorical` - Human Categorical * `human_boolean` - Human Boolean * `human_text` - Human Text * `custom` - Custom
    - `score_value_type` 'numerical' | 'boolean' | 'percentage' | 'single_select' | 'multi_select' | 'text' | 'json' | 'comment' | 'categorical' — * `numerical` - Numerical * `boolean` - Boolean * `percentage` - Percentage * `single_select` - Single Select * `multi_select` - Multi Select * `text` - Text * `json` - Json * `comment` - Comment * `categorical` - Categorical
    - `eval_class` union
      - 'ragas_faithfulness' | 'ragas_noise_sensitivity' | 'ragas_response_relevancy' | 'ragas_answer_relevancy' | 'ragas_context_precision' | 'ragas_context_recall' | 'ragas_context_entity_recall' | 'ragas_factual_correctness' | 'ragas_semantic_similarity' | 'ragas_non_llm_string_similarity' | 'ragas_non_llm_string_presence' | 'ragas_non_llm_exact_match' | 'relari_llm_based_custom_metric' | 'relari_llm_based_answer_correctness' | 'keywordsai_custom_evaluator' | 'keywordsai_custom_llm' | 'output_char_count' | 'output_word_count' | 'custom_code' — * `ragas_faithfulness` - ragas_faithfulness * `ragas_noise_sensitivity` - ragas_noise_sensitivity * `ragas_response_relevancy` - ragas_response_relevancy * `ragas_answer_relevancy` - ragas_answer_relevancy * `ragas_context_precision` - ragas_context_precision * `ragas_context_recall` - ragas_context_recall * `ragas_context_entity_recall` - ragas_context_entity_recall * `ragas_factual_correctness` - ragas_factual_correctness * `ragas_semantic_similarity` - ragas_semantic_similarity * `ragas_non_llm_string_similarity` - ragas_non_llm_string_similarity * `ragas_non_llm_string_presence` - ragas_non_llm_string_presence * `ragas_non_llm_exact_match` - ragas_non_llm_exact_match * `relari_llm_based_custom_metric` - relari_llm_based_custom_metric * `relari_llm_based_answer_correctness` - relari_llm_based_answer_correctness * `keywordsai_custom_evaluator` - keywordsai_custom_evaluator * `keywordsai_custom_llm` - keywordsai_custom_llm * `output_char_count` - output_char_count * `output_word_count` - output_word_count * `custom_code` - custom_code
      - ''
    - `custom_required_fields` string[]
    - `starred` boolean

---

[API](https://skmtc.net/keywordsai/apis/api-reference.md) · [All operations](https://skmtc.net/keywordsai/apis/api-reference/llms.txt) · [OpenAPI document](https://skmtc-service-staging.skmtc.workers.dev/v1/apis/keywordsai/api-reference/versions/c26d550029f8/schema)