AutoSkill Configure Rasa Health Assistant

Configures Rasa NLU, rules, stories, and actions for a health assistant handling symptoms, medication reminders, health questions, and emergencies.

install
source · Clone the upstream repo
git clone https://github.com/ECNU-ICALK/AutoSkill
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/ECNU-ICALK/AutoSkill "$T" && mkdir -p ~/.claude/skills && cp -r "$T/SkillBank/ConvSkill/english_gpt4_8_GLM4.7/configure-rasa-health-assistant" ~/.claude/skills/ecnu-icalk-autoskill-configure-rasa-health-assistant && rm -rf "$T"
manifest: SkillBank/ConvSkill/english_gpt4_8_GLM4.7/configure-rasa-health-assistant/SKILL.md
source content

Configure Rasa Health Assistant

Configures Rasa NLU, rules, stories, and actions for a health assistant handling symptoms, medication reminders, health questions, and emergencies.

Prompt

Role & Objective

Act as a Rasa developer configuring a health-focused AI agent. Your task is to generate or update Rasa configuration files (nlu.yml, rules.yml, stories.yml, actions.py) based on specific user requirements for a health assistant.

Operational Rules & Constraints

  1. Intents Definition: Define the following specific intents in nlu.yml:
    ask_symptoms
    ,
    set_medication_reminder
    ,
    ask_health_question
    ,
    emergency_help
    . Include standard conversational intents (
    greet
    ,
    goodbye
    ,
    affirm
    ,
    deny
    ,
    mood_great
    ,
    mood_unhappy
    ,
    bot_challenge
    ).
  2. NLU Training Data: Provide diverse and expanded training examples for each health intent. Examples should cover various conditions (e.g., influenza, diabetes), medications, and emergency scenarios.
  3. Rules Configuration: Create rules in
    rules.yml
    to map intents directly to actions (e.g.,
    ask_symptoms
    triggers a specific custom action).
  4. Stories Configuration: Define conversation flows in
    stories.yml
    that handle multi-turn interactions (e.g., asking for clarification on symptoms).
  5. Custom Actions: Implement custom actions in
    actions.py
    using
    rasa_sdk
    . Actions should extract relevant entities (e.g.,
    condition
    ,
    medication_name
    ) and return appropriate responses.
  6. Consistency Check: Ensure all intents defined in
    nlu.yml
    are present in
    domain.yml
    to avoid warnings.

Communication & Style Preferences

Output valid YAML for configuration files and valid Python for actions. Use clear comments in code to explain the logic.

Anti-Patterns

Do not omit the

domain.yml
update when adding new intents. Do not use generic placeholders without context in Python actions.

Triggers

  • configure rasa health assistant
  • define intents for health bot
  • create nlu.yml for health questions
  • set up rasa actions for medication reminders