Agent skill · research science · erichowens
crisis-detection-intervention-ai
Detect crisis signals in user content using NLP, mental health sentiment analysis, and safe intervention protocols. Implements suicide ideation detection, automated escalation, and crisis resource
Why this skill is useful
Adds specialized NLP models and crisis intervention protocols that significantly enhance the AI's ability to detect and respond to mental health crises.
What it needs
Requires npm installed locally. About 7k tokens when loaded. Last updated 2026-07-14. 180 stars on the source repository.
What this skill does
Crisis Detection & Intervention AI Expert in detecting mental health crises and implementing safe, ethical intervention protocols. ⚠️ ETHICAL DISCLAIMER This skill assists with crisis detection, NOT crisis response. ✅ Appropriate uses: Flagging concerning content for human review Connecting users to professional resources Escalating to crisis counselors Providing immediate hotline information ❌ NOT a substitute for: Licensed therapists Emergency services (911) Medical diagnosis Professional mental health treatment Always provide crisis hotlines: National Suicide Prevention Lifeline: 988 --- When to Use ✅ Use for: Mental health journaling apps Recovery community platforms Support group monitoring Online therapy platforms Crisis text line integration ❌ NOT for: General sentiment analysis (use standard tools) Medical diagnosis (not qualified) Automated responses without human review Replacing professional crisis counselors Quick Decision Tree --- Technology Selection NLP Models for Mental Health (2024) Model Best For Accuracy Latency ------- ---------- ---------- --------- MentalBERT Mental health text 89% 50ms GPT-4 + Few-shot Crisis detection 92% 200ms RoBERTa-Mental Depression detection 87% 40ms Custom Fine-tuned BERT Domain-specific 90%+ 60ms Timeline: 2019: BERT fine-tuned for mental health 2021: MentalBERT released 2023: GPT-4 shows strong zero-shot crisis detection 2024: Specialized models for specific conditions --- Common Anti-Patterns Anti-Pattern 1: Using Generic Sentiment Analysis Novice thinking: "Negative sentiment = crisis" Problem: Mental health language is nuanced, context-dependent. Wrong approach: Why wrong: "I'm tired" vs "I'm tired of living" - different meanings, same sentiment. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills erichowens/crisis-detection-intervention-ai