<｜begin▁of▁sentence｜>### Instruction:
Imagine you're working with a smart canine training platform, where there's an 'no_filter' feature that's been designed to accept a wide variety of dog training session data without imposing any restrictions. To streamline the process, you want to digitize the feature's blueprint, which currently includes a rundown of its purpose, an unpopulated list anticipating data fields that could be utilized in the future, and a blank template for evaluation criteria.

Could you ponder on the best method to transcribe this 'no_filter' feature's framework into a digital JSON format, ensuring it fully encapsulates the essence of a feature that's flexible and unrestrictive, much like the training tactics you might use for a dog with a unique set of skills? 

Please note that if this 'no_filter' feature were to be comparable to a GML file that guides dogs through a virtual obstacle course, it would be titled something akin to "no_filter_training_plan.gml". For our purposes, however, the data we're considering is purely hypothetical and doesn't have any specific content to include.
### Response:
import json

# Define the data structure for no_filter API
api_data = {
    'Description': 'This is a placeholder API that accepts any input and does not apply any filtering logic.',
    'Field List': {},
    'Rubrics': {}
}

# Convert the data structure to a JSON object
api_json = json.dumps(api_data)

print(api_json)
<|EOT|>
