import requests
url = "https://app.oneperfectslice.ai/api/public/v1/slices/{key}"
headers = {"Authorization": "Bearer <token>"}
response = requests.get(url, headers=headers)
print(response.text){
"data": {
"key": "high_intent_deals",
"title": "High-Intent Deals",
"objective": "pipeline",
"description": "Surfaces deals showing strong buying signals.",
"elementKeys": [
"intent_signal",
"budget_confirmation"
],
"outputSchema": {},
"preferredModel": "gpt-5-mini",
"includeCrmData": true,
"evidenceGrouping": "ByElement"
}
}Returns the complete definition for a single slice, including its output schema, preferred model, and evidence grouping strategy. Use this to understand what a slice produces before running it.
import requests
url = "https://app.oneperfectslice.ai/api/public/v1/slices/{key}"
headers = {"Authorization": "Bearer <token>"}
response = requests.get(url, headers=headers)
print(response.text){
"data": {
"key": "high_intent_deals",
"title": "High-Intent Deals",
"objective": "pipeline",
"description": "Surfaces deals showing strong buying signals.",
"elementKeys": [
"intent_signal",
"budget_confirmation"
],
"outputSchema": {},
"preferredModel": "gpt-5-mini",
"includeCrmData": true,
"evidenceGrouping": "ByElement"
}
}Documentation Index
Fetch the complete documentation index at: https://docs.oneperfectslice.ai/llms.txt
Use this file to discover all available pages before exploring further.
outputSchema field tells you the exact shape of the structured result you’ll get when a run completes. Use it to plan how your integration handles the output.