Create a pool

Creates a pool.

The pool is automatically assigned an ID.

Restriction. You can send a maximum of 20 requests of this kind per minute and 100 requests per day.

Note. Learn about creating a training pool in Create a training pool.

Request

POST https://toloka.yandex.com/api/v1/pools
Authorization: OAuth <OAuth token>
Content-Type: application/JSON

POST https://sandbox.toloka.yandex.com/api/v1/pools
Authorization: OAuth <OAuth token>
Content-Type: application/JSON

Headers


Title	Overview
authorization	A token for account authorization. Add OAuth as a prefix.
content-type	Specifies the data format in the request body.

Request body

{
  "project_id": "1",
  "private_name": "My first pool",
  "private_comment": "This is my first pool",
  "public_description": "Pool's description ",
  "may_contain_adult_content": false,
  "will_expire": "2020-09-01T13:00",
  "reward_per_assignment": 0.02,
  "dynamic_pricing_config": {
    "type": "SKILL",
    "skill_id": "1289",
    "intervals": [
      {
        "from": 0,
        "to": 60,
        "reward_per_assignment": 0.03
      },
      {
        "from": 61,
        "to": 100,
        "reward_per_assignment": 0.04
      }
    ]
  },
  "assignment_max_duration_seconds": 300,
  "auto_accept_solutions": true,
  "auto_accept_period_day": 7,
  "auto_close_after_complete_delay_seconds": 60,
  "assignments_issuing_config": {
    "issue_task_suites_in_creation_order": false
  },
  "filter": {<settings for filtering users>},
  "quality_control": {
    "training_requirement": {
      "training_pool_id": "21",
      "training_passing_skill_value": 70
    },
    "captcha_frequency": "LOW",
    "configs": {<quality control rule settings>},
    "checkpoints_config": {
      "real_settings": {
        "target_overlap": 5,
        "task_distribution_function": {
          "scope": "PROJECT",
          "distribution": "UNIFORM",
          "window_days": 7,
          "intervals": [
            {
              "from": 1,
              "to": 100,
              "frequency": 5
            },
            {
              "from": 101,
              "to": 1000,
              "frequency": 25
            }
          ]
        }
      },
      "golden_settings": {
        "target_overlap": 5,
        "task_distribution_function": {
          "scope": "PROJECT",
          "distribution": "UNIFORM",
          "window_days": 7,
          "intervals": [
            {
              "from": 1,
              "to": 100,
              "frequency": 5
            },
            {
              "from": 101,
              "to": 1000,
              "frequency": 25
            }
          ]
        }
      },
      "training_settings": {
        "target_overlap": 5,
        "task_distribution_function": {
          "scope": "PROJECT",
          "distribution": "UNIFORM",
          "window_days": 7,
          "intervals": [
            {
              "from": 1,
              "to": 100,
              "frequency": 5
            },
            {
              "from": 101,
              "to": 1000,
              "frequency": 25
            }
          ]
        }
      }
    }
  },
  "dynamic_overlap_config": {
    "type": "BASIC",
    "max_overlap": 5,
    "min_confidence": 0.9,
    "answer_weight_skill_id": "1289",
    "fields": [
      {
        "name": "result"
      }
    ]
  },
  "defaults" : {
    "default_overlap_for_new_task_suites" : 3,
    "default_overlap_for_new_tasks": 3
  },
  "mixer_config": {
    "real_tasks_count": 6,
    "golden_tasks_count": 1,
    "training_tasks_count": 1,
    "min_real_tasks_count": 2,
    "min_golden_tasks_count": 0,
    "min_training_tasks_count": 0,
    "force_last_assignment": true,
    "force_last_assignment_delay_seconds": 10,
    "mix_tasks_in_creation_order": true,
    "shuffle_tasks_in_task_suite": false,
    "golden_task_distribution_function": {
      "scope": "PROJECT",
      "distribution": "UNIFORM",
      "window_days": 7 ,
      "intervals": [
        {
          "from": 1,
          "to": 25,
          "frequency": 5
        },
        {
          "from": 26,
          "to": 1000,
          "frequency": 25
        }
      ]
    },
    "training_task_distribution_function": {
      "scope": "PROJECT",
      "distribution": "UNIFORM",
      "window_days": 7,
      "intervals": [
        {
          "from": 1,
          "to": 25,
          "frequency": 5
        },
        {
          "from": 26,
          "to": 1000,
          "frequency": 25
        }
      ]
    }
  },
  "priority": 10
}
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Parameter	Overview
project_id	string \| required ID of the project that the pool was created for.
private_name	string \| required Name of the pool (only visible to the requester).
may_contain_adult_content	boolean \| required Whether the tasks contain adult content.
will_expire	string \| required The date and time in UTC when the pool should be closed (even if all the task suites haven't been completed). It uses ISO 8601 format: YYYY-MM-DDThh:mm:ss[.sss].
reward_per_assignment	float \| required Payment per task suite in U.S. dollars. For cents, use the dot (".") as the separator. The minimum payment is $0.01. Only training and control tasks can be uploaded to zero-price pools.
defaults	object \| required Settings that are applied by default when uploading new task suites to a pool.
defaults.default_overlap_ for_new_task_suites	integer \| required The overlap for task suites that are uploaded to the pool (used if the `allow_defaults=true` parameter is set at upload).
assignment_max_duration_ seconds	integer \| required The time allowed for completing a task suite, in seconds. Tasks not completed within this time are reassigned to other users. We recommend allowing no more than 60 seconds per task suite (including the time for loading the page and submitting responses).
dynamic_pricing_config.type	string \| required if Required if dynamic pricing is used. Parameter type for calculating dynamic pricing. The `SKILL` value.
dynamic_pricing_config. skill_id	string \| required if Required if dynamic pricing is used. ID of the skill that the task price is based on.
dynamic_pricing_config. intervals[]	array of objects \| required if Required if dynamic pricing is used. Skill level intervals. Must not overlap. A performer with a skill level that is not included in any interval will receive the basic price for a task suite.
dynamic_pricing_config. intervals[].from	integer \| required if Required if dynamic pricing is used. Lower bound of the interval. May take a value from 0 to 100. By default `0`.
dynamic_pricing_config. intervals[].to	integer \| required if Required if dynamic pricing is used. Upper bound of the interval. May take a value from 0 to 100. By default `100`.
dynamic_pricing_config. intervals[].reward_per_ assignment	float \| required if Required if dynamic pricing is used. The price per task suite for a performer with the specified skill level.
quality_control. checkpoints_config. real_settings. target_overlap	integer \| required if Required if selective review is used. Overlap in tasks with selective review.
quality_control. checkpoints_config. real_settings. task_distribution_function	object \| required if Required if selective review is used. Distribution of tasks with selective review.
quality_control. checkpoints_config. real_settings. task_distribution_function. scope	string \| required if Required if selective review is used. How to count tasks completed by the user: `POOL` — Count completed pool tasks. `PROJECT` — Count completed project tasks.
quality_control. checkpoints_config. real_settings. task_distribution_function. distribution	string \| required if Required if selective review is used. Distribution of tasks with selective review within an interval. This parameter has only one possible value — `UNIFORM`.
quality_control. checkpoints_config. real_settings. task_distribution_function. window_days	integer \| required if Required if selective review is used. Period in which completed tasks are counted (number of days).
quality_control. checkpoints_config. real_settings. task_distribution_function. intervals[]	array of objects \| required if Required if selective review is used. Interval limits and frequency of tasks with selective review.
quality_control. checkpoints_config. real_settings. task_distribution_function. intervals[].from	integer \| required if Required if selective review is used. Start of the interval (number of tasks completed by the user in the project or in the pool).
quality_control. checkpoints_config. real_settings. task_distribution_function. intervals[].to	integer \| required if Required if selective review is used. End of the interval (number of tasks completed by the user in the project or in the pool).
quality_control. checkpoints_config. real_settings. task_distribution_function. intervals[].frequency	integer \| required if Required if selective review is used. Frequency of tasks with selective review within an interval. The first task in an interval is a majority vote task. For example, if you set `frequency: 3`, then tasks number 1, 4, 7, and so on, will be majority vote tasks.
quality_control. checkpoints_config. golden_settings. target_overlap	integer \| required if Required if selective review is used. Overlap in control tasks with selective review.
quality_control. checkpoints_config. golden_settings. task_distribution_function	object \| required if Required if selective review is used. Distribution of control tasks with selective review.
quality_control. checkpoints_config. golden_settings. task_distribution_function. scope	string \| required if Required if selective review is used. How to count tasks completed by the user: `POOL` — Count completed pool tasks. `PROJECT` — Count completed project tasks.
quality_control. checkpoints_config. golden_settings. task_distribution_function	string \| required if Required if selective review is used. Distribution of control tasks with selective review within an interval. This parameter has only one possible value — `UNIFORM`.
quality_control. checkpoints_config. golden_settings. task_distribution_function. window_days	integer \| required if Required if selective review is used. Period in which completed tasks are counted (number of days).
quality_control. checkpoints_config. golden_settings. task_distribution_function. intervals[]	array of objects \| required if Required if selective review is used. Interval limits and frequency of control tasks with selective review.
quality_control. checkpoints_config. golden_settings. task_distribution_function. intervals[].from	integer \| required if Required if selective review is used. Start of the interval (number of tasks completed by the user in the project or in the pool).
quality_control. checkpoints_config. golden_settings. task_distribution_function. intervals[].to	integer \| required if Required if selective review is used. End of the interval (number of tasks completed by the user in the project or in the pool).
quality_control. checkpoints_config. golden_settings. task_distribution_function. intervals[].frequency	integer \| required if Required if selective review is used. Frequency of control tasks with selective review within an interval. The first task in an interval is a majority vote task. For example, if you set `frequency: 3`, then tasks number 1, 4, 7, and so on, will be majority vote tasks.
quality_control. checkpoints_config. training_settings. target_overlap	integer \| required if Required if selective review is used. Overlap in training tasks with selective review.
quality_control. checkpoints_config. training_settings. task_distribution_function	object \| required if Required if selective review is used. Distribution of training tasks with selective review.
quality_control. checkpoints_config. training_settings. task_distribution_function. scope	string \| required if Required if selective review is used. How to count tasks completed by the user: `POOL` — Count completed pool tasks. `PROJECT` — Count completed project tasks.
quality_control. checkpoints_config. training_settings. task_distribution_function. distribution	string \| required if Required if selective review is used. Distribution of training tasks with selective review within an interval. This parameter has only one possible value — `UNIFORM`.
quality_control. checkpoints_config. training_settings. task_distribution_function. window_days	integer \| required if Required if selective review is used. Period in which completed tasks are counted (number of days).
quality_control. checkpoints_config. training_settings. task_distribution_function. intervals[]	array of objects \| required if Required if selective review is used. Interval limits and frequency of training tasks with selective review.
quality_control. checkpoints_config. training_settings. task_distribution_function. intervals[].from	integer \| required if Required if selective review is used. Start of the interval (number of tasks completed by the user in the project or in the pool).
quality_control. checkpoints_config. training_settings. task_distribution_function. intervals[].to	integer \| required if Required if selective review is used. End of the interval (number of tasks completed by the user in the project or in the pool).
quality_control. checkpoints_config. training_settings. task_distribution_function. intervals[].frequency	integer \| required if Required if selective review is used. Frequency of training tasks with selective review within an interval. The first task in an interval is a majority vote task. For example, if you set `frequency: 3`, then tasks number 1, 4, 7, and so on, will be majority vote tasks.
dynamic_overlap_config.type	string \| required if Required if dynamic overlap is used. The algorithm for dynamic overlap. `BASIC` — Each response is assigned a weight depending on the performer's skill value. The aggregated response confidence is calculated based on the probability algorithm. The task overlap increases until it reaches `max_overlap` or until the confidence of the aggregated response exceeds `min_confidence`. You have to specify `max_overlap`, `min_confidence`, `answer_weight_skill_id` and `fields`.
dynamic_overlap_config. max_overlap	integer \| required if Required if dynamic overlap is used. Maximum overlap. Must be higher than the values in `defaults`. Minimum — 1. Maximum — 30000.
dynamic_overlap_config. min_confidence	float \| required if Required if dynamic overlap is used. Minimum confidence of the aggregated response. Values from 0 to 1.
dynamic_overlap_config. answer_weight_skill_id	string \| required if Required if dynamic overlap is used. A skill that determines the weight of the performer's response. For best results, use a skill calculated as the percentage of correct responses in control tasks.
dynamic_overlap_config. fields	object \| required if Required if dynamic overlap is used. Output data fields to use for aggregating responses. For best results, each of these fields must have a limited number of response options. Don't specify several fields if their values depend on each other.
dynamic_overlap_config. fields.name	string \| required if Required if dynamic overlap is used. The output data field name.
mixer_config	object \| required if Required if “smart mixing” is used. Parameters for automatically creating a task suite (“smart mixing”). For more information about creating task suites, see the Requester's guide.
mixer_config. real_tasks_count	integer \| required if Required if “smart mixing” is used. Number of main tasks per suite. The maximum number of tasks per task suite if `golden_task_distribution_function` or `training_task_distribution_function` is used.
mixer_config. golden_tasks_count	integer \| required if Required if “smart mixing” is used. Number of control tasks per suite.
mixer_config. training_tasks_count	integer \| required if Required if “smart mixing” is used. Number of training tasks per suite.
mixer_config.golden_task_ distribution_function.scope	string \| required if Required if control tasks are assigned at a variable rate. How to count tasks completed by the user: `POOL` — Count completed pool tasks. `PROJECT` — Count completed project tasks.
mixer_config.golden_task_ distribution_function. distribution	string \| required if Required if control tasks are assigned at a variable rate. Distribution of control tasks within an interval. This parameter has only one possible value — `UNIFORM`.
mixer_config.golden_task_ distribution_function. window_days	integer \| required if Required if control tasks are assigned at a variable rate. Period in which completed tasks are counted (number of days).
mixer_config.golden_task_ distribution_function. intervals[]	array of objects \| required if Required if control tasks are assigned at a variable rate. Interval borders and number of control tasks in an interval.
mixer_config.golden_task_ distribution_function. intervals[].from	integer \| required if Required if control tasks are assigned at a variable rate. Start of the interval (number of tasks completed by the user in the project or in the pool).
mixer_config.golden_task_ distribution_function. intervals[].to	integer \| required if Required if control tasks are assigned at a variable rate. End of the interval (number of tasks completed by the user in the project or in the pool).
mixer_config.golden_task_ distribution_function. intervals[].frequency	integer \| required if Required if control tasks are assigned at a variable rate. Frequency of control tasks in an interval. The first task in an interval is a control task. For example, if you set `frequency: 3` tasks number 1, 4, 7 and so on will be control tasks.
mixer_config.training_task_ distribution_function.scope	string \| required if Required if training tasks are assigned at a variable rate. How to count tasks completed by the user: `POOL` — Count completed pool tasks. `PROJECT` — Count completed project tasks.
mixer_config.training_task_ distribution_function. distribution	string \| required if Required if training tasks are assigned at a variable rate. Distribution of training tasks within an interval. This parameter has only one possible value — `UNIFORM`.
mixer_config.training_task_ distribution_function. window_days	integer \| required if Required if training tasks are assigned at a variable rate. Period in which completed tasks are counted (number of days).
mixer_config.training_task_ distribution_function. intervals[]	array of objects \| required if Required if training tasks are assigned at a variable rate. Interval borders and number of control tasks in an interval.
mixer_config.training_task_ distribution_function. intervals[].from	integer \| required if Required if training tasks are assigned at a variable rate. Start of the interval (number of tasks completed by the user in the project or in the pool). Yes, if you use uneven distribution of training tasks
mixer_config.training_task_ distribution_function. intervals[].to	integer \| required if Required if training tasks are assigned at a variable rate. End of the interval (number of tasks completed by the user in the project or in the pool).
mixer_config.training_task_ distribution_function. intervals[].frequency	integer \| required if Required if training tasks are assigned at a variable rate. Frequency of training tasks in an interval. The first task in an interval is a training task. For example, if you set `frequency: 3` tasks number 1, 4, 7 and so on will be training tasks.
private_comment	string Comments on the pool (only visible to the requester).
public_description	string Description for users. If it is filled in, the text will be displayed instead of the project's `public_description` in the list of tasks for performers.
dynamic_pricing_config	object Dynamic pricing settings.
auto_accept_solutions	boolean Whether tasks must be checked manually: `true` — Automatic task acceptance (manual checking isn't necessary). false — The requester will check the tasks. The default value is `true`.
auto_accept_period_day	integer Time (number of days) for the requester to review the task. If the requester doesn't accept or reject the task within this period, the decision will be made automatically. May take a value from 1 to 21.
auto_close_after_complete_ delay_seconds	integer Waiting time (in seconds) before automatic closure of the pool after all tasks are completed. Minimum — 0, maximum — 259,200 seconds (three days). The default value is 0. Use it if: Your data processing is close to real time. You need an open pool where you upload tasks. Dynamic overlap is enabled in the pool (`dynamic_overlap_config`).
assignments_issuing_config	object Settings for assigning tasks in the pool.
assignments_issuing_config. issue_task_suites_in_ creation_order	boolean For pools that don't use “smart mixing” . Assign task suites in the order in which they were uploaded. For example, for a pool with an overlap of 5, the first task suite is assigned to five users, then the second task suite, and so on. This parameter is available when the project has `"assignments_issuing_type": "AUTOMATED".`
Priority	integer The priority of the pool in relation to other pools in the project with the same task price and set of filters. Users are assigned tasks with a higher priority first. Possible values: from `-100` to `100`. By default the value is `0` .
filter	object Settings for user selection filters.
quality_control	object Settings for quality control rules and the ID of the pool with training tasks.
quality_control. training_requirement	object Parameters of the training pool that is linked to the main task pool.
quality_control. training_requirement. training_pool_id	string ID of the training pool that is linked to the main task pool.
quality_control. training_requirement. training_passing_skill_value	integer Percentage of correct answers in training tasks (from 0 to 100) required in order to access the main tasks. Only the first answer of the user in each task is taken into account.
quality_control. captcha_frequency	string The frequency of showing captchas: `LOW` — Show one for every 20 tasks. `MEDIUM`, `HIGH` — Show one for every 10 tasks. By default, captchas aren't displayed.
quality_control.configs	object Quality control rules.
quality_control. checkpoints_config	object Selective task review. If you want to use the majority vote quality control method, specify `MAJORITY_VOTE` in the quality_control parameter. Some tasks are assigned with higher overlap (for example, “5”) and checked. The rest of the tasks are assigned with the overlap set for the pool (for example, “1”) and they are not checked. Selective review lets you improve pool completion quality. You can reduce the frequency of checking tasks over time. Example of settings: in the first 100 tasks completed by the user in the pool, assign every 5th task with an overlap of “5” to check matching responses. In the following tasks, every 25th task is issued with an overlap of “5”.
quality_control. checkpoints_config. real_settings	object Selective review of main tasks. To make sure selective review is enabled, don't forget to set up task display in mixer_config.
quality_control. checkpoints_config. golden_settings	object Selective review of control tasks. To make sure selective review is enabled, don't forget to set up display of this type of task in mixer_config.
quality_control. checkpoints_config. training_settings	object Selective review of training tasks. To make sure selective review is enabled, don't forget to set up display of this type of task in mixer_config.
dynamic_overlap_config	object Setting up dynamic overlap (also known as incremental relabeling or IRL). Allows you to change the overlap depending on how well the performers handle the task. Set the closing interval (`auto_close_after_complete_delay_seconds`). It should be enough to complete tasks with an overlap higher than the minimum. When all pool tasks are completed, aggregate the responses.
defaults.default_overlap_ for_new_tasks	integer The overlap for tasks that are uploaded to the pool (used if the `allow_defaults=true` parameter is set at upload).
mixer_config. min_real_tasks_count	float Minimum number of main tasks in a task suite (if the number of assignments left is less than the number specified in `mixer_config.real_tasks_count`). Minimum — 0. By default, the value is the same as in `mixer_config.real_tasks_count`.
mixer_config. min_golden_tasks_count	integer Minimum number of control tasks per task suite (if the number of assignments left is less than the number specified in `mixer_config.golden_tasks_count`). Minimum — 0. By default, the value is the same as in `mixer_config.golden_tasks_count`.
mixer_config. min_training_tasks_count	integer Minimum number of training tasks per task suite (if the number of assignments left is less than the number specified in `mixer_config.golden_tasks_count`). Minimum — 0. By default, the value is the same as in `mixer_config.training_tasks_count`.
mixer_config. force_last_assignment	boolean Setting for the last task suite in the pool, if less than the minimum remaining number of tasks are not completed (`mixer_config.min_real_tasks_count`). Values: `true` — Assign an incomplete task suite. `false` — Don't assign tasks. This option can be used if you are adding tasks after the pool is started. The default value is `true`. This parameter only applies to main tasks. The number of control and training tasks in the last suite must be complete (`mixer_config.golden_tasks_count`, `mixer_config.training_tasks_count`).
mixer_config.force_last_ assignment_ delay_seconds	integer Waiting time (in seconds) after adding a task or increasing the overlap before assigning the last task suite in the pool. Minimum — 0, maximum — 86,400 seconds (one day). This parameter can be used if the pool has `force_last_assignment: true`.
mixer_config.mix_tasks_ in_creation_ order	boolean The order used to add tasks to suites: `true` — Add tasks to suites in the order in which they were uploaded. For example, in a pool with an overlap of 5, the first uploaded task will be included in the first 5 task suites. They will be assigned to 5 users. `false` — Add tasks to suites in random order. The default value is `false`.
mixer_config. shuffle_tasks_in_task_suite	boolean The order of tasks within a suite: `true` — Random. `false` — The order in which tasks were uploaded. The default value is `true`.
mixer_config.golden_task_ distribution_function	object Vary the frequency of control tasks. The option allows you to change the frequency of checking as the user completes more tasks. If it is filled in, use `real_task_count` to specify the maximum number of tasks per task suite. To use the option, set the `golden_task_count:0` and `min_golden_tasks_count:null` parameter values. The interval bound is the number of a task in the pool. If the task suite has several intervals, the settings for the first interval are applied. Example: In the first task suite (the range from 1 to 25), every fifth task is a control task, and in the following suites, every 25th task is a control task.
mixer_config.training_task_ distribution_function	object Issue of training tasks with uneven frequency. This option allows you to change the frequency of training tasks as the user completes more tasks. If it is filled in, use `real_task_count` to specify the maximum number of tasks per task suite. To use the option, set parameter values `training_task_count:0` and `min_training_tasks_count:null`. Example: In the first task suite (the range from 1 to 25), every fifth task is a training task, and in the following suites, every 25th task is a training task.


Parameter	Overview
project_id	string \| required ID of the project that the pool was created for.
private_name	string \| required Name of the pool (only visible to the requester).
may_contain_adult_content	boolean \| required Whether the tasks contain adult content.
will_expire	string \| required The date and time in UTC when the pool should be closed (even if all the task suites haven't been completed). It uses ISO 8601 format: YYYY-MM-DDThh:mm:ss[.sss].
reward_per_assignment	float \| required Payment per task suite in U.S. dollars. For cents, use the dot (".") as the separator. The minimum payment is $0.01. Only training and control tasks can be uploaded to zero-price pools.
defaults	object \| required Settings that are applied by default when uploading new task suites to a pool.
defaults.default_overlap_ for_new_task_suites	integer \| required The overlap for task suites that are uploaded to the pool (used if the `allow_defaults=true` parameter is set at upload).
assignment_max_duration_ seconds	integer \| required The time allowed for completing a task suite, in seconds. Tasks not completed within this time are reassigned to other users. We recommend allowing no more than 60 seconds per task suite (including the time for loading the page and submitting responses).
dynamic_pricing_config.type	string \| required if Required if dynamic pricing is used. Parameter type for calculating dynamic pricing. The `SKILL` value.
dynamic_pricing_config. skill_id	string \| required if Required if dynamic pricing is used. ID of the skill that the task price is based on.
dynamic_pricing_config. intervals[]	array of objects \| required if Required if dynamic pricing is used. Skill level intervals. Must not overlap. A performer with a skill level that is not included in any interval will receive the basic price for a task suite.
dynamic_pricing_config. intervals[].from	integer \| required if Required if dynamic pricing is used. Lower bound of the interval. May take a value from 0 to 100. By default `0`.
dynamic_pricing_config. intervals[].to	integer \| required if Required if dynamic pricing is used. Upper bound of the interval. May take a value from 0 to 100. By default `100`.
dynamic_pricing_config. intervals[].reward_per_ assignment	float \| required if Required if dynamic pricing is used. The price per task suite for a performer with the specified skill level.
quality_control. checkpoints_config. real_settings. target_overlap	integer \| required if Required if selective review is used. Overlap in tasks with selective review.
quality_control. checkpoints_config. real_settings. task_distribution_function	object \| required if Required if selective review is used. Distribution of tasks with selective review.
quality_control. checkpoints_config. real_settings. task_distribution_function. scope	string \| required if Required if selective review is used. How to count tasks completed by the user: `POOL` — Count completed pool tasks. `PROJECT` — Count completed project tasks.
quality_control. checkpoints_config. real_settings. task_distribution_function. distribution	string \| required if Required if selective review is used. Distribution of tasks with selective review within an interval. This parameter has only one possible value — `UNIFORM`.
quality_control. checkpoints_config. real_settings. task_distribution_function. window_days	integer \| required if Required if selective review is used. Period in which completed tasks are counted (number of days).
quality_control. checkpoints_config. real_settings. task_distribution_function. intervals[]	array of objects \| required if Required if selective review is used. Interval limits and frequency of tasks with selective review.
quality_control. checkpoints_config. real_settings. task_distribution_function. intervals[].from	integer \| required if Required if selective review is used. Start of the interval (number of tasks completed by the user in the project or in the pool).
quality_control. checkpoints_config. real_settings. task_distribution_function. intervals[].to	integer \| required if Required if selective review is used. End of the interval (number of tasks completed by the user in the project or in the pool).
quality_control. checkpoints_config. real_settings. task_distribution_function. intervals[].frequency	integer \| required if Required if selective review is used. Frequency of tasks with selective review within an interval. The first task in an interval is a majority vote task. For example, if you set `frequency: 3`, then tasks number 1, 4, 7, and so on, will be majority vote tasks.
quality_control. checkpoints_config. golden_settings. target_overlap	integer \| required if Required if selective review is used. Overlap in control tasks with selective review.
quality_control. checkpoints_config. golden_settings. task_distribution_function	object \| required if Required if selective review is used. Distribution of control tasks with selective review.
quality_control. checkpoints_config. golden_settings. task_distribution_function. scope	string \| required if Required if selective review is used. How to count tasks completed by the user: `POOL` — Count completed pool tasks. `PROJECT` — Count completed project tasks.
quality_control. checkpoints_config. golden_settings. task_distribution_function	string \| required if Required if selective review is used. Distribution of control tasks with selective review within an interval. This parameter has only one possible value — `UNIFORM`.
quality_control. checkpoints_config. golden_settings. task_distribution_function. window_days	integer \| required if Required if selective review is used. Period in which completed tasks are counted (number of days).
quality_control. checkpoints_config. golden_settings. task_distribution_function. intervals[]	array of objects \| required if Required if selective review is used. Interval limits and frequency of control tasks with selective review.
quality_control. checkpoints_config. golden_settings. task_distribution_function. intervals[].from	integer \| required if Required if selective review is used. Start of the interval (number of tasks completed by the user in the project or in the pool).
quality_control. checkpoints_config. golden_settings. task_distribution_function. intervals[].to	integer \| required if Required if selective review is used. End of the interval (number of tasks completed by the user in the project or in the pool).
quality_control. checkpoints_config. golden_settings. task_distribution_function. intervals[].frequency	integer \| required if Required if selective review is used. Frequency of control tasks with selective review within an interval. The first task in an interval is a majority vote task. For example, if you set `frequency: 3`, then tasks number 1, 4, 7, and so on, will be majority vote tasks.
quality_control. checkpoints_config. training_settings. target_overlap	integer \| required if Required if selective review is used. Overlap in training tasks with selective review.
quality_control. checkpoints_config. training_settings. task_distribution_function	object \| required if Required if selective review is used. Distribution of training tasks with selective review.
quality_control. checkpoints_config. training_settings. task_distribution_function. scope	string \| required if Required if selective review is used. How to count tasks completed by the user: `POOL` — Count completed pool tasks. `PROJECT` — Count completed project tasks.
quality_control. checkpoints_config. training_settings. task_distribution_function. distribution	string \| required if Required if selective review is used. Distribution of training tasks with selective review within an interval. This parameter has only one possible value — `UNIFORM`.
quality_control. checkpoints_config. training_settings. task_distribution_function. window_days	integer \| required if Required if selective review is used. Period in which completed tasks are counted (number of days).
quality_control. checkpoints_config. training_settings. task_distribution_function. intervals[]	array of objects \| required if Required if selective review is used. Interval limits and frequency of training tasks with selective review.
quality_control. checkpoints_config. training_settings. task_distribution_function. intervals[].from	integer \| required if Required if selective review is used. Start of the interval (number of tasks completed by the user in the project or in the pool).
quality_control. checkpoints_config. training_settings. task_distribution_function. intervals[].to	integer \| required if Required if selective review is used. End of the interval (number of tasks completed by the user in the project or in the pool).
quality_control. checkpoints_config. training_settings. task_distribution_function. intervals[].frequency	integer \| required if Required if selective review is used. Frequency of training tasks with selective review within an interval. The first task in an interval is a majority vote task. For example, if you set `frequency: 3`, then tasks number 1, 4, 7, and so on, will be majority vote tasks.
dynamic_overlap_config.type	string \| required if Required if dynamic overlap is used. The algorithm for dynamic overlap. `BASIC` — Each response is assigned a weight depending on the performer's skill value. The aggregated response confidence is calculated based on the probability algorithm. The task overlap increases until it reaches `max_overlap` or until the confidence of the aggregated response exceeds `min_confidence`. You have to specify `max_overlap`, `min_confidence`, `answer_weight_skill_id` and `fields`.
dynamic_overlap_config. max_overlap	integer \| required if Required if dynamic overlap is used. Maximum overlap. Must be higher than the values in `defaults`. Minimum — 1. Maximum — 30000.
dynamic_overlap_config. min_confidence	float \| required if Required if dynamic overlap is used. Minimum confidence of the aggregated response. Values from 0 to 1.
dynamic_overlap_config. answer_weight_skill_id	string \| required if Required if dynamic overlap is used. A skill that determines the weight of the performer's response. For best results, use a skill calculated as the percentage of correct responses in control tasks.
dynamic_overlap_config. fields	object \| required if Required if dynamic overlap is used. Output data fields to use for aggregating responses. For best results, each of these fields must have a limited number of response options. Don't specify several fields if their values depend on each other.
dynamic_overlap_config. fields.name	string \| required if Required if dynamic overlap is used. The output data field name.
mixer_config	object \| required if Required if “smart mixing” is used. Parameters for automatically creating a task suite (“smart mixing”). For more information about creating task suites, see the Requester's guide.
mixer_config. real_tasks_count	integer \| required if Required if “smart mixing” is used. Number of main tasks per suite. The maximum number of tasks per task suite if `golden_task_distribution_function` or `training_task_distribution_function` is used.
mixer_config. golden_tasks_count	integer \| required if Required if “smart mixing” is used. Number of control tasks per suite.
mixer_config. training_tasks_count	integer \| required if Required if “smart mixing” is used. Number of training tasks per suite.
mixer_config.golden_task_ distribution_function.scope	string \| required if Required if control tasks are assigned at a variable rate. How to count tasks completed by the user: `POOL` — Count completed pool tasks. `PROJECT` — Count completed project tasks.
mixer_config.golden_task_ distribution_function. distribution	string \| required if Required if control tasks are assigned at a variable rate. Distribution of control tasks within an interval. This parameter has only one possible value — `UNIFORM`.
mixer_config.golden_task_ distribution_function. window_days	integer \| required if Required if control tasks are assigned at a variable rate. Period in which completed tasks are counted (number of days).
mixer_config.golden_task_ distribution_function. intervals[]	array of objects \| required if Required if control tasks are assigned at a variable rate. Interval borders and number of control tasks in an interval.
mixer_config.golden_task_ distribution_function. intervals[].from	integer \| required if Required if control tasks are assigned at a variable rate. Start of the interval (number of tasks completed by the user in the project or in the pool).
mixer_config.golden_task_ distribution_function. intervals[].to	integer \| required if Required if control tasks are assigned at a variable rate. End of the interval (number of tasks completed by the user in the project or in the pool).
mixer_config.golden_task_ distribution_function. intervals[].frequency	integer \| required if Required if control tasks are assigned at a variable rate. Frequency of control tasks in an interval. The first task in an interval is a control task. For example, if you set `frequency: 3` tasks number 1, 4, 7 and so on will be control tasks.
mixer_config.training_task_ distribution_function.scope	string \| required if Required if training tasks are assigned at a variable rate. How to count tasks completed by the user: `POOL` — Count completed pool tasks. `PROJECT` — Count completed project tasks.
mixer_config.training_task_ distribution_function. distribution	string \| required if Required if training tasks are assigned at a variable rate. Distribution of training tasks within an interval. This parameter has only one possible value — `UNIFORM`.
mixer_config.training_task_ distribution_function. window_days	integer \| required if Required if training tasks are assigned at a variable rate. Period in which completed tasks are counted (number of days).
mixer_config.training_task_ distribution_function. intervals[]	array of objects \| required if Required if training tasks are assigned at a variable rate. Interval borders and number of control tasks in an interval.
mixer_config.training_task_ distribution_function. intervals[].from	integer \| required if Required if training tasks are assigned at a variable rate. Start of the interval (number of tasks completed by the user in the project or in the pool). Yes, if you use uneven distribution of training tasks
mixer_config.training_task_ distribution_function. intervals[].to	integer \| required if Required if training tasks are assigned at a variable rate. End of the interval (number of tasks completed by the user in the project or in the pool).
mixer_config.training_task_ distribution_function. intervals[].frequency	integer \| required if Required if training tasks are assigned at a variable rate. Frequency of training tasks in an interval. The first task in an interval is a training task. For example, if you set `frequency: 3` tasks number 1, 4, 7 and so on will be training tasks.
private_comment	string Comments on the pool (only visible to the requester).
public_description	string Description for users. If it is filled in, the text will be displayed instead of the project's `public_description` in the list of tasks for performers.
dynamic_pricing_config	object Dynamic pricing settings.
auto_accept_solutions	boolean Whether tasks must be checked manually: `true` — Automatic task acceptance (manual checking isn't necessary). false — The requester will check the tasks. The default value is `true`.
auto_accept_period_day	integer Time (number of days) for the requester to review the task. If the requester doesn't accept or reject the task within this period, the decision will be made automatically. May take a value from 1 to 21.
auto_close_after_complete_ delay_seconds	integer Waiting time (in seconds) before automatic closure of the pool after all tasks are completed. Minimum — 0, maximum — 259,200 seconds (three days). The default value is 0. Use it if: Your data processing is close to real time. You need an open pool where you upload tasks. Dynamic overlap is enabled in the pool (`dynamic_overlap_config`).
assignments_issuing_config	object Settings for assigning tasks in the pool.
assignments_issuing_config. issue_task_suites_in_ creation_order	boolean For pools that don't use “smart mixing” . Assign task suites in the order in which they were uploaded. For example, for a pool with an overlap of 5, the first task suite is assigned to five users, then the second task suite, and so on. This parameter is available when the project has `"assignments_issuing_type": "AUTOMATED".`
Priority	integer The priority of the pool in relation to other pools in the project with the same task price and set of filters. Users are assigned tasks with a higher priority first. Possible values: from `-100` to `100`. By default the value is `0` .
filter	object Settings for user selection filters.
quality_control	object Settings for quality control rules and the ID of the pool with training tasks.
quality_control. training_requirement	object Parameters of the training pool that is linked to the main task pool.
quality_control. training_requirement. training_pool_id	string ID of the training pool that is linked to the main task pool.
quality_control. training_requirement. training_passing_skill_value	integer Percentage of correct answers in training tasks (from 0 to 100) required in order to access the main tasks. Only the first answer of the user in each task is taken into account.
quality_control. captcha_frequency	string The frequency of showing captchas: `LOW` — Show one for every 20 tasks. `MEDIUM`, `HIGH` — Show one for every 10 tasks. By default, captchas aren't displayed.
quality_control.configs	object Quality control rules.
quality_control. checkpoints_config	object Selective task review. If you want to use the majority vote quality control method, specify `MAJORITY_VOTE` in the quality_control parameter. Some tasks are assigned with higher overlap (for example, “5”) and checked. The rest of the tasks are assigned with the overlap set for the pool (for example, “1”) and they are not checked. Selective review lets you improve pool completion quality. You can reduce the frequency of checking tasks over time. Example of settings: in the first 100 tasks completed by the user in the pool, assign every 5th task with an overlap of “5” to check matching responses. In the following tasks, every 25th task is issued with an overlap of “5”.
quality_control. checkpoints_config. real_settings	object Selective review of main tasks. To make sure selective review is enabled, don't forget to set up task display in mixer_config.
quality_control. checkpoints_config. golden_settings	object Selective review of control tasks. To make sure selective review is enabled, don't forget to set up display of this type of task in mixer_config.
quality_control. checkpoints_config. training_settings	object Selective review of training tasks. To make sure selective review is enabled, don't forget to set up display of this type of task in mixer_config.
dynamic_overlap_config	object Setting up dynamic overlap (also known as incremental relabeling or IRL). Allows you to change the overlap depending on how well the performers handle the task. Set the closing interval (`auto_close_after_complete_delay_seconds`). It should be enough to complete tasks with an overlap higher than the minimum. When all pool tasks are completed, aggregate the responses.
defaults.default_overlap_ for_new_tasks	integer The overlap for tasks that are uploaded to the pool (used if the `allow_defaults=true` parameter is set at upload).
mixer_config. min_real_tasks_count	float Minimum number of main tasks in a task suite (if the number of assignments left is less than the number specified in `mixer_config.real_tasks_count`). Minimum — 0. By default, the value is the same as in `mixer_config.real_tasks_count`.
mixer_config. min_golden_tasks_count	integer Minimum number of control tasks per task suite (if the number of assignments left is less than the number specified in `mixer_config.golden_tasks_count`). Minimum — 0. By default, the value is the same as in `mixer_config.golden_tasks_count`.
mixer_config. min_training_tasks_count	integer Minimum number of training tasks per task suite (if the number of assignments left is less than the number specified in `mixer_config.golden_tasks_count`). Minimum — 0. By default, the value is the same as in `mixer_config.training_tasks_count`.
mixer_config. force_last_assignment	boolean Setting for the last task suite in the pool, if less than the minimum remaining number of tasks are not completed (`mixer_config.min_real_tasks_count`). Values: `true` — Assign an incomplete task suite. `false` — Don't assign tasks. This option can be used if you are adding tasks after the pool is started. The default value is `true`. This parameter only applies to main tasks. The number of control and training tasks in the last suite must be complete (`mixer_config.golden_tasks_count`, `mixer_config.training_tasks_count`).
mixer_config.force_last_ assignment_ delay_seconds	integer Waiting time (in seconds) after adding a task or increasing the overlap before assigning the last task suite in the pool. Minimum — 0, maximum — 86,400 seconds (one day). This parameter can be used if the pool has `force_last_assignment: true`.
mixer_config.mix_tasks_ in_creation_ order	boolean The order used to add tasks to suites: `true` — Add tasks to suites in the order in which they were uploaded. For example, in a pool with an overlap of 5, the first uploaded task will be included in the first 5 task suites. They will be assigned to 5 users. `false` — Add tasks to suites in random order. The default value is `false`.
mixer_config. shuffle_tasks_in_task_suite	boolean The order of tasks within a suite: `true` — Random. `false` — The order in which tasks were uploaded. The default value is `true`.
mixer_config.golden_task_ distribution_function	object Vary the frequency of control tasks. The option allows you to change the frequency of checking as the user completes more tasks. If it is filled in, use `real_task_count` to specify the maximum number of tasks per task suite. To use the option, set the `golden_task_count:0` and `min_golden_tasks_count:null` parameter values. The interval bound is the number of a task in the pool. If the task suite has several intervals, the settings for the first interval are applied. Example: In the first task suite (the range from 1 to 25), every fifth task is a control task, and in the following suites, every 25th task is a control task.
mixer_config.training_task_ distribution_function	object Issue of training tasks with uneven frequency. This option allows you to change the frequency of training tasks as the user completes more tasks. If it is filled in, use `real_task_count` to specify the maximum number of tasks per task suite. To use the option, set parameter values `training_task_count:0` and `min_training_tasks_count:null`. Example: In the first task suite (the range from 1 to 25), every fifth task is a training task, and in the following suites, every 25th task is a training task.

Response

Contains information about the created training pool. Besides parameters that are set when creating a training pool, it includes parameters that are assigned to the pool automatically:


Parameter	Overview
id	string Pool ID.
status	string Status of the pool: `OPEN` — Open. `CLOSED` — Closed. `ARCHIVED` — Archived.
last_close_reason	string The reason for closing the pool the last time: `MANUAL` — Closed by the requester. `EXPIRED` — Reached the date and time set in `will_expire`. `COMPLETED` — Closed automatically because all the pool tasks were completed. `NOT_ENOUGH_BALANCE` — Closed automatically because the Toloka account ran out of funds. `ASSIGNMENTS_LIMIT_EXCEEDED` — Closed automatically because it exceeded the limit on assigned task suites (2 million maximum). `BLOCKED` — Closed automatically because the requester's account was blocked by a Toloka administrator. `FOR_UPDATE` — The pool is closed for editing.
created	string The UTC date and time when the pool was created, in ISO 8601 format: YYYY-MM-DDThh:mm:ss[.sss].
last_started	string The date and time when the pool was last started, in UTC in ISO 8601 format: YYYY-MM-DDThh:mm:ss[.sss].
last_stopped	string The date and time when the pool was last stopped, in UTC in ISO 8601 format: YYYY-MM-DDThh:mm:ss[.sss].
type	string Types of pool: `REGULAR` - normal pool; `TRAINING` - training pool.


Parameter	Overview
id	string Pool ID.
status	string Status of the pool: `OPEN` — Open. `CLOSED` — Closed. `ARCHIVED` — Archived.
last_close_reason	string The reason for closing the pool the last time: `MANUAL` — Closed by the requester. `EXPIRED` — Reached the date and time set in `will_expire`. `COMPLETED` — Closed automatically because all the pool tasks were completed. `NOT_ENOUGH_BALANCE` — Closed automatically because the Toloka account ran out of funds. `ASSIGNMENTS_LIMIT_EXCEEDED` — Closed automatically because it exceeded the limit on assigned task suites (2 million maximum). `BLOCKED` — Closed automatically because the requester's account was blocked by a Toloka administrator. `FOR_UPDATE` — The pool is closed for editing.
created	string The UTC date and time when the pool was created, in ISO 8601 format: YYYY-MM-DDThh:mm:ss[.sss].
last_started	string The date and time when the pool was last started, in UTC in ISO 8601 format: YYYY-MM-DDThh:mm:ss[.sss].
last_stopped	string The date and time when the pool was last stopped, in UTC in ISO 8601 format: YYYY-MM-DDThh:mm:ss[.sss].
type	string Types of pool: `REGULAR` - normal pool; `TRAINING` - training pool.