Agent skill

Crisis Detection Intervention AI

by curiositech in curiositech/some_claude_skills

Detect crisis signals in user content using NLP, mental health sentiment analysis, and safe intervention protocols.

MITAuto-check passedProductivity & Automation

Install Crisis Detection Intervention AI

skills CLI
$ npx skills add curiositech/some_claude_skills --skill crisis-detection-intervention-ai -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install curiositech/some_claude_skills crisis-detection-intervention-ai --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/curiositech/some_claude_skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/crisis-detection-intervention-ai .claude/skills/crisis-detection-intervention-ai && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
crisis-detection-intervention-ai
GitHub stars
244
Used in
2 other repos
Token cost
~3.8k tokens
SKILL.md length
456 words
Files
7 (incl. scripts, references)
Skills in repo
95
Repo updated
First seen
Licence
MIT

At a glance

Detect crisis signals in user content using NLP, mental health sentiment analysis, and safe intervention protocols.

  • Mental health apps
  • SKILL.md covers ⚠️ ETHICAL DISCLAIMER, When to Use, Quick Decision Tree and Technology Selection, plus 6 more sections
  • Runs TypeScript scripts from its folder; reaches 988lifeline.org; needs CRISIS_DATA_KEY and ANTHROPIC_API_KEY
  • Recovery platforms

What it does

Crisis Detection Intervention AI is an agent skill from curiositech/some_claude_skills. 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 integration. Use for mental health apps, recovery platforms, support communities. Activate on "crisis detection", "suicide prevention", "mental health NLP", "intervention protocol". NOT for general sentiment analysis, medical diagnosis, or replacing professional help.

Its SKILL.md is about 3.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 9 other files, including scripts and reference files (for example `.claude-plugin/plugin.json`, `references/crisis-resources.md` and `references/intervention-protocols.md`).

It sits in Productivity & Automation, covering Health and fitness tracking, Customer feedback analysis and Natural language processing. The repository describes itself as: Claude skills that make my life easier. The licence is MIT.

When your agent uses it

  • Mental health apps
  • Recovery platforms
  • Support communities

Example prompts

  • “crisis detection”
  • “suicide prevention”
  • “mental health NLP”
  • “/crisis-detection-intervention-ai”

Requirements

  • Node.js
  • A credential in CRISIS_DATA_KEY
  • Pre-approved tools (allowed-tools): Read, Write, Edit, Bash(npm:*)

What it can do on your machine

Read from SKILL.md and the folder at commit 6713fc7. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Write
    • Edit
    • Bash(npm:*)

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 2 files in scripts/ (TypeScript), which the agent can run.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • 988lifeline.org

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • CRISIS_DATA_KEY
    • ANTHROPIC_API_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Crisis Detection Intervention AI loads about 3.8k tokens when it runs, and up to ~12k if it reads all its reference files. Until then it costs about 125 tokens; SKILL.md has 456 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~125
When it runs · the whole SKILL.md, loaded when a task matches
~3.8k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~12k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from curiositech/some_claude_skills at commit 6713fc7, republished under its MIT licence (© curiositech). 456 words, ~3,807 tokens.

Download SKILL.mdSave it as .claude/skills/crisis-detection-intervention-ai/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.
name
crisis-detection-intervention-ai
description
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 integration. Use for mental health apps, recovery platforms, support communities. Activate on "crisis detection", "suicide prevention", "mental health NLP", "intervention protocol". NOT for general sentiment analysis, medical diagnosis, or replacing professional help.
allowed-tools
Read, Write, Edit, Bash(npm:*)
metadata.category
Lifestyle & Personal
metadata.tags
crisis, detection, intervention, crisis-detection, suicide-prevention

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

Detected concerning content?
├── Immediate danger? → Escalate to crisis counselor + show 988
├── Suicidal ideation? → Flag for review + show resources
├── Substance relapse? → Connect to sponsor + resources
├── Self-harm mention? → Gentle check-in + resources
└── General distress? → Supportive response + resources

Technology Selection

NLP Models for Mental Health (2024)
ModelBest ForAccuracyLatency
MentalBERTMental health text89%50ms
GPT-4 + Few-shotCrisis detection92%200ms
RoBERTa-MentalDepression detection87%40ms
Custom Fine-tuned BERTDomain-specific90%+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:

typescript
// ❌ Generic sentiment misses mental health signals
const sentiment = analyzeSentiment(text);

if (sentiment.score < -0.5) {
  alertCrisis();  // Too broad!
}

Why wrong: "I'm tired" vs "I'm tired of living" - different meanings, same sentiment.

Correct approach:

typescript
// ✅ Mental health-specific model
import { pipeline } from '@huggingface/transformers';

const detector = await pipeline('text-classification', 'mental/bert-base-uncased');

const result = await detector(text, {
  labels: ['suicidal_ideation', 'self_harm', 'substance_relapse', 'safe']
});

if (result[0].label === 'suicidal_ideation' && result[0].score > 0.8) {
  await escalateToCrisisCounselor({
    text,
    confidence: result[0].score,
    timestamp: Date.now()
  });

  // IMMEDIATELY show crisis resources
  showCrisisResources({
    phone: '988',
    text: 'Text "HELLO" to 741741',
    chat: 'https://988lifeline.org/chat'
  });
}

Timeline context:

  • 2015: Rule-based keyword matching
  • 2020: BERT fine-tuning for mental health
  • 2024: Multi-label models with context understanding

Anti-Pattern 2: Automated Responses Without Human Review

Problem: AI cannot replace empathy, may escalate distress.

Wrong approach:

typescript
// ❌ AI auto-responds to crisis
if (isCrisis(text)) {
  await sendMessage(userId, "I'm concerned about you. Are you okay?");
}

Why wrong:

  • Feels robotic, invalidating
  • May increase distress
  • No human judgment

Correct approach:

typescript
// ✅ Flag for human review, show resources
if (isCrisis(text)) {
  // 1. Flag for counselor review
  await flagForReview({
    userId,
    text,
    severity: 'high',
    detectedAt: Date.now(),
    requiresImmediate: true
  });

  // 2. Notify on-call counselor
  await notifyOnCallCounselor({
    userId,
    summary: 'Suicidal ideation detected',
    urgency: 'immediate'
  });

  // 3. Show resources (no AI message)
  await showInAppResources({
    type: 'crisis_support',
    resources: [
      { name: '988 Suicide & Crisis Lifeline', link: 'tel:988' },
      { name: 'Crisis Text Line', link: 'sms:741741' },
      { name: 'Chat Now', link: 'https://988lifeline.org/chat' }
    ]
  });

  // 4. DO NOT send automated "are you okay" message
}

Human review flow:

AI Detection → Flag → On-call counselor notified → Human reaches out

Show full SKILL.md (191 more words)Show less
Anti-Pattern 3: Not Providing Immediate Resources

Problem: User in crisis needs help NOW, not later.

Wrong approach:

typescript
// ❌ Just flags, no immediate help
if (isCrisis(text)) {
  await logCrisisEvent(userId, text);
  // User left with no resources
}

Correct approach:

typescript
// ✅ Immediate resources + escalation
if (isCrisis(text)) {
  // Show resources IMMEDIATELY (blocking modal)
  await showCrisisModal({
    title: 'Resources Available',
    resources: [
      {
        name: '988 Suicide & Crisis Lifeline',
        description: 'Free, confidential support 24/7',
        action: 'tel:988',
        type: 'phone'
      },
      {
        name: 'Crisis Text Line',
        description: 'Text support with trained counselor',
        action: 'sms:741741',
        message: 'HELLO',
        type: 'text'
      },
      {
        name: 'Chat with counselor',
        description: 'Online chat support',
        action: 'https://988lifeline.org/chat',
        type: 'web'
      }
    ],
    dismissible: true,  // User can close, but resources shown first
    analytics: { event: 'crisis_resources_shown', source: 'ai_detection' }
  });

  // Then flag for follow-up
  await flagForReview({ userId, text, severity: 'high' });
}

Anti-Pattern 4: Storing Crisis Data Insecurely

Problem: Crisis content is extremely sensitive PHI.

Wrong approach:

typescript
// ❌ Plain text storage
await db.logs.insert({
  userId: user.id,
  type: 'crisis',
  content: text,  // Stored in plain text!
  timestamp: Date.now()
});

Why wrong: Data breach exposes most vulnerable moments.

Correct approach:

typescript
// ✅ Encrypted, access-logged, auto-deleted
import { encrypt, decrypt } from './encryption';

await db.crisisEvents.insert({
  id: generateId(),
  userId: hashUserId(user.id),  // Hash, not plain ID
  contentHash: hashContent(text),  // For deduplication only
  encryptedContent: encrypt(text, process.env.CRISIS_DATA_KEY),
  detectedAt: Date.now(),
  reviewedAt: null,
  reviewedBy: null,
  autoDeleteAt: Date.now() + (30 * 24 * 60 * 60 * 1000),  // 30 days
  accessLog: []
});

// Log all access
await logAccess({
  eventId: crisisEvent.id,
  accessedBy: counselorId,
  accessedAt: Date.now(),
  reason: 'Review for follow-up',
  ipAddress: hashedIp
});

// Auto-delete after retention period
schedule.daily(() => {
  db.crisisEvents.deleteMany({
    autoDeleteAt: { $lt: Date.now() }
  });
});

HIPAA Requirements:

  • Encryption at rest and in transit
  • Access logging
  • Auto-deletion after retention period
  • Minimum necessary access

Anti-Pattern 5: No Escalation Protocol

Problem: No clear path from detection to human intervention.

Wrong approach:

typescript
// ❌ Flags crisis but no escalation process
if (isCrisis(text)) {
  await db.flags.insert({ userId, text, flaggedAt: Date.now() });
  // Now what? Who responds?
}

Correct approach:

typescript
// ✅ Clear escalation protocol
enum CrisisSeverity {
  LOW = 'low',        // Distress, no immediate danger
  MEDIUM = 'medium',  // Self-harm thoughts, no plan
  HIGH = 'high',      // Suicidal ideation with plan
  IMMEDIATE = 'immediate'  // Imminent danger
}

async function escalateCrisis(detection: CrisisDetection): Promise<void> {
  const severity = assessSeverity(detection);

  switch (severity) {
    case CrisisSeverity.IMMEDIATE:
      // Notify on-call counselor (push notification)
      await notifyOnCall({
        userId: detection.userId,
        severity,
        requiresResponse: 'immediate',
        text: detection.text
      });

      // Send SMS to backup on-call if no response in 5 min
      setTimeout(async () => {
        if (!await hasResponded(detection.id)) {
          await notifyBackupOnCall(detection);
        }
      }, 5 * 60 * 1000);

      // Show 988 modal (blocking)
      await show988Modal(detection.userId);
      break;

    case CrisisSeverity.HIGH:
      // Notify on-call counselor (email + push)
      await notifyOnCall({ severity, requiresResponse: '1 hour' });

      // Show crisis resources
      await showCrisisResources(detection.userId);
      break;

    case CrisisSeverity.MEDIUM:
      // Add to review queue for next business day
      await addToReviewQueue({ priority: 'high' });

      // Suggest self-help resources
      await suggestResources(detection.userId, 'coping_strategies');
      break;

    case CrisisSeverity.LOW:
      // Add to review queue
      await addToReviewQueue({ priority: 'normal' });
      break;
  }

  // Always log for audit
  await logEscalation({
    detectionId: detection.id,
    severity,
    actions: ['notified_on_call', 'showed_resources'],
    timestamp: Date.now()
  });
}

Implementation Patterns

Pattern 1: Multi-Signal Detection
typescript
interface CrisisSignal {
  type: 'suicidal_ideation' | 'self_harm' | 'substance_relapse' | 'severe_distress';
  confidence: number;
  evidence: string[];
}

async function detectCrisisSignals(text: string): Promise<CrisisSignal[]> {
  const signals: CrisisSignal[] = [];

  // Signal 1: NLP model
  const nlpResult = await mentalHealthNLP(text);
  if (nlpResult.score > 0.75) {
    signals.push({
      type: nlpResult.label,
      confidence: nlpResult.score,
      evidence: ['NLP model detection']
    });
  }

  // Signal 2: Keyword matching (backup)
  const keywords = detectKeywords(text);
  if (keywords.length > 0) {
    signals.push({
      type: 'suicidal_ideation',
      confidence: 0.6,
      evidence: keywords
    });
  }

  // Signal 3: Sentiment + context
  const sentiment = await sentimentAnalysis(text);
  const hasHopelessness = /no (hope|point|reason|future)/i.test(text);

  if (sentiment.score < -0.8 && hasHopelessness) {
    signals.push({
      type: 'severe_distress',
      confidence: 0.7,
      evidence: ['Extreme negative sentiment + hopelessness language']
    });
  }

  return signals;
}
Pattern 2: Safe Keyword Matching
typescript
const CRISIS_KEYWORDS = {
  suicidal_ideation: [
    /\b(kill|end|take)\s+(my|own)\s+life\b/i,
    /\bsuicide\b/i,
    /\bdon'?t\s+want\s+to\s+(live|be here|exist)\b/i,
    /\bbetter off dead\b/i
  ],
  self_harm: [
    /\b(cut|cutting|hurt)\s+(myself|me)\b/i,
    /\bself[- ]harm\b/i
  ],
  substance_relapse: [
    /\b(relapsed|used|drank)\s+(again|today)\b/i,
    /\bback on\s+(drugs|alcohol)\b/i
  ]
};

function detectKeywords(text: string): string[] {
  const matches: string[] = [];

  for (const [type, patterns] of Object.entries(CRISIS_KEYWORDS)) {
    for (const pattern of patterns) {
      if (pattern.test(text)) {
        matches.push(type);
      }
    }
  }

  return [...new Set(matches)];  // Deduplicate
}
Pattern 3: GPT-4 Few-Shot Detection
typescript
import Anthropic from '@anthropic-ai/sdk';

const client = new Anthropic({ apiKey: process.env.ANTHROPIC_API_KEY });

async function detectWithClaude(text: string): Promise<CrisisDetection> {
  const response = await client.messages.create({
    model: 'claude-3-5-sonnet-20241022',
    max_tokens: 200,
    messages: [{
      role: 'user',
      content: `You are a mental health crisis detection system. Analyze this text for crisis signals.

Text: "${text}"

Respond in JSON:
{
  "is_crisis": boolean,
  "severity": "none" | "low" | "medium" | "high" | "immediate",
  "signals": ["suicidal_ideation" | "self_harm" | "substance_relapse"],
  "confidence": 0.0-1.0,
  "reasoning": "brief explanation"
}

Examples:
- "I'm thinking about ending it all" → { "is_crisis": true, "severity": "high", "signals": ["suicidal_ideation"], "confidence": 0.95 }
- "I relapsed today, feeling ashamed" → { "is_crisis": true, "severity": "medium", "signals": ["substance_relapse"], "confidence": 0.9 }
- "Had a tough day at work" → { "is_crisis": false, "severity": "none", "signals": [], "confidence": 0.95 }`
    }]
  });

  const result = JSON.parse(response.content[0].text);
  return result;
}

Production Checklist

□ Mental health-specific NLP model (not generic sentiment)
□ Human review required before automated action
□ Crisis resources shown IMMEDIATELY (988, text line)
□ Clear escalation protocol (severity-based)
□ Encrypted storage of crisis content
□ Access logging for all crisis data access
□ Auto-deletion after retention period (30 days)
□ On-call counselor notification system
□ Backup notification if no response
□ False positive tracking (improve model)
□ Regular model evaluation with experts
□ Ethics review board approval

When to Use vs Avoid

ScenarioAppropriate?
Journaling app for recovery✅ Yes - monitor for relapses
Support group chat✅ Yes - flag concerning posts
Therapy platform messages✅ Yes - assist therapists
Public social media❌ No - privacy concerns
Replace human counselors❌ Never - AI assists, doesn't replace
Medical diagnosis❌ Never - not qualified

References

  • /references/mental-health-nlp.md - NLP models for mental health
  • /references/intervention-protocols.md - Evidence-based intervention strategies
  • /references/crisis-resources.md - Hotlines, text lines, and support services

Scripts

  • scripts/crisis_detector.ts - Real-time crisis detection system
  • scripts/model_evaluator.ts - Evaluate detection accuracy with test cases

This skill guides: Crisis detection | Mental health NLP | Intervention protocols | Suicide prevention | HIPAA compliance | Ethical AI

© curiositech, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 6 other files (scripts, references) in .claude/skills/crisis-detection-intervention-ai of curiositech/some_claude_skills.

  • SKILL.md
  • .claude-plugin/plugin.json
  • references/crisis-resources.md
  • references/intervention-protocols.md
  • references/mental-health-nlp.md
  • scripts/crisis_detector.ts
  • scripts/model_evaluator.ts

Open the folder on GitHubat commit 6713fc7

Used in 2 other repositories

We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in curiositech/some_claude_skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

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Azure AI Textanalytics Pymicrosoft/skills3.1k5 repos~2.4kAutomated safety check: PassMIT
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Sentiment AnalysisDrchronx/ai-agent-research-starter-kit139—~516Automated safety check: PassCustom licence

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Questions about Crisis Detection Intervention AI

What does Crisis Detection Intervention AI do?

Detect crisis signals in user content using NLP, mental health sentiment analysis, and safe intervention protocols. Crisis Detection Intervention AI is an agent skill from curiositech/some_claude_skills. Detect crisis signals in user content using NLP, mental health sentiment analysis, and safe intervention protocols.

When should I use Crisis Detection Intervention AI?

Crisis Detection Intervention AI fits situations like: mental health apps; recovery platforms; support communities.

How do I install Crisis Detection Intervention AI in Claude Code?

Run `npx skills add curiositech/some_claude_skills --skill crisis-detection-intervention-ai -a claude-code`. Or copy the skill folder (.claude/skills/crisis-detection-intervention-ai in curiositech/some_claude_skills) into .claude/skills/crisis-detection-intervention-ai in your project. Claude Code loads it when a task matches its description.

How do I install Crisis Detection Intervention AI in Codex?

Run `npx skills add curiositech/some_claude_skills --skill crisis-detection-intervention-ai -a codex`. Or copy the skill folder (.claude/skills/crisis-detection-intervention-ai in curiositech/some_claude_skills) into .agents/skills/crisis-detection-intervention-ai in your project. Codex loads it when a task matches its description.

Can I use Crisis Detection Intervention AI in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add curiositech/some_claude_skills --skill crisis-detection-intervention-ai -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/crisis-detection-intervention-ai, .gemini/skills/crisis-detection-intervention-ai, .github/skills/crisis-detection-intervention-ai and .opencode/skills/crisis-detection-intervention-ai in your project.

What does Crisis Detection Intervention AI need to run?

Going by SKILL.md and its folder, Crisis Detection Intervention AI needs TypeScript for the scripts in its folder and credentials named CRISIS_DATA_KEY and ANTHROPIC_API_KEY. Our summary lists: Node.js; A credential in CRISIS_DATA_KEY. Its frontmatter pre-approves these tools: Read, Write, Edit, Bash(npm:*).

Does Crisis Detection Intervention AI access the network?

SKILL.md names 1 domain. In commands or code: 988lifeline.org; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Crisis Detection Intervention AI safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Crisis Detection Intervention AI use?

Crisis Detection Intervention AI is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Crisis Detection Intervention AI use?

About 3.8k tokens (SKILL.md is roughly 15k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 7.7k tokens, read only when the agent opens those files.

What are the alternatives to Crisis Detection Intervention AI?

Skills that share tags, products or a category with Crisis Detection Intervention AI: Content Analysis (liangdabiao/claude-data-analysis-ultra-main, 290 stars), Azure AI Textanalytics Py (microsoft/skills, 3.1k stars), Trend To Product Mapper (MaxKmet/idea-validation-agents, 478 stars) and Analyzing Text With NLP (jeremylongshore/tons-of-skills-marketplace, 2.8k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Crisis Detection Intervention AI?

curiositech (a GitHub organization) maintains it in curiositech/some_claude_skills, which has 244 GitHub stars. The repository holds 95 skills in this directory. The repository was last updated on September 6, 2026.

Source: curiositech/some_claude_skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.