Analyze Intent and Entities
Analyze a text message and return the intents, entities, and traits inferred by Wit.ai.
/oo Wit.ai: Analyze text [text] with Wit.ai and explain returned intents, entities, and confidence values.
Provide a sample message to inspect its predicted intent and entities, or compare the detected language candidates.
Copy a prompt into your agent with the oo Skill installed. Add your page links and source notes before running it.
Analyze a text message and return the intents, entities, and traits inferred by Wit.ai.
/oo Wit.ai: Analyze text [text] with Wit.ai and explain returned intents, entities, and confidence values.
Detect the most likely locales for a text message using Wit.ai language identification.
/oo Wit.ai: Detect the language of [text] and report the returned candidates and confidence.
Set up oo CLI and the oo Skill in your agent.
Install OOMOL →Connect with the Server Access Token from your Wit.ai app settings.
Connect Wit.ai →Use /oo with the pages to read, the changes to make, and where to save the result.
Connection Guide →Choose Your Agent
Wit.ai analyzes text using the connected app’s model and definitions. The integration also exposes app configuration and training-data operations for explicit requests.
Analyze a text message and return the intents, entities, and traits inferred by Wit.ai.
Detect the most likely locales for a text message using Wit.ai language identification.
Analyze a text message and return the intents, entities, and traits inferred by Wit.ai.
wit_ai.analyze_message Detect the most likely locales for a text message using Wit.ai language identification.
wit_ai.detect_language List the Wit.ai apps accessible by the current bearer token.
wit_ai.list_apps Retrieve details and training status for a specific Wit.ai app.
wit_ai.get_app List all intents defined in the current Wit.ai app.
wit_ai.list_intents Create a new Wit.ai intent for labeling user messages.
wit_ai.create_intent Retrieve a Wit.ai intent together with the entity bindings it uses.
wit_ai.get_intent List all entities defined in the current Wit.ai app.
wit_ai.list_entities Create a new Wit.ai entity with optional lookups and keywords.
wit_ai.create_entity Retrieve a Wit.ai entity including its roles, lookups, and keywords.
wit_ai.get_entity Update a Wit.ai entity by sending the desired end-state definition for its schema and keywords.
wit_ai.update_entity Add a keyword and optional synonyms to an existing Wit.ai entity.
wit_ai.add_entity_keyword Add a synonym to a specific keyword on a Wit.ai entity.
wit_ai.add_keyword_synonym List all traits defined in the current Wit.ai app.
wit_ai.list_traits Create a new Wit.ai trait with one or more canonical values.
wit_ai.create_trait Retrieve a Wit.ai trait together with its configured values.
wit_ai.get_trait Add a canonical value to an existing Wit.ai trait.
wit_ai.add_trait_value List validated utterances already stored in the current Wit.ai app.
wit_ai.list_utterances Asynchronously enqueue validated utterances for training in Wit.ai.
wit_ai.create_utterances Asynchronously delete validated utterances from the current Wit.ai app.
wit_ai.delete_utterances No matching tools.
Use AI to explain Wit.ai intent, entity, and language predictions for text messages.
Text analysis returns predictions based on the app’s model; it does not run the business actions implied by an intent.
Copy the Server Access Token from your Wit.ai app settings. Intent predictions depend on the definitions and training of that app.
Manage which optional storage OOMOL can use. You can change these choices from the footer at any time.