Overview
Generate actionable improvement suggestions for your text. This analyzes your content and provides specific, prioritized recommendations to enhance quality and conversion potential. The endpoint is POST /api/ult
; the request body sets action: "nudges"
.
Parameters
Ruleset to use (for example product_description
).
Input text (max 5,000 characters).
Number of suggestions to return (minimum 1).
Example
curl -X POST https://whetdata.com/api/ult \
-H "x-api-key: whet_your_api_key_here" \
-H "Content-Type: application/json" \
-d '{
"action": "nudges",
"ruleset": "product_description",
"text": "This product is good and works well.",
"max_nudges": 3
}'
title: “Nudges”
openapi: “POST /api/ult”
Overview
The nudges
action generates actionable improvement suggestions for your text. It analyzes your content and provides specific, prioritized recommendations to enhance quality and conversion potential.
Use This Action To
- Improve existing product descriptions
- Generate variations for A/B testing
- Identify gaps in your content strategy
- Learn what makes effective copy
Parameters
Ruleset name for analysis (e.g., product_descriptions
, marketing_copy
,
technical_docs
, reviews
)
Text to improve (max 5,000 characters)
Maximum number of nudges to generate (minimum: 1)
Tips
Start by requesting 3-5 nudges initially. Focus on high-priority suggestions
first for maximum impact.
The maximum text length is 5,000 characters. For longer texts, split them into
chunks.
Your Whetdata API key. Get a free key here.
action
enum<string>
default:classification
required
Action type: classification | nudges | clean
Available options:
classification
,
nudges
,
clean
text
string
default:Premium wireless headphones with active noise cancellation, 30-hour battery life, and crystal-clear audio quality.
required
Input text (max 5,000 characters)
Maximum length: 5000
ruleset
enum<string>
default:product_description
Ruleset name (required for classification and nudges)
Available options:
product
,
product_description
,
marketing_copy
,
product_review
,
technical_documentation
,
date_online
Classification threshold (0.0 to 1.0)
Required range: 0 <= x <= 1
Option 1
Option 2
Option 3