# AI Community Toxic Comment Classifier

> Classify toxic comments by type, assign severity scores, and recommend response strategies. Use when the user needs community moderation, toxicity detection, or automated comment handling for forums, Discord, or WordPress.

- Skill: `ncreighton/ai-community-toxic-comment-classifier` (Agent Skill)
- Install (CLI): `npx skillmds@latest add ncreighton/ai-community-toxic-comment-classifier`
- Raw SKILL.md: https://api.skillmd.com/api/skills/ncreighton/ai-community-toxic-comment-classifier/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: ncreighton (https://skillmd.com/u/ncreighton)
- Updated: 2026-09-10
- Page: https://skillmd.com/skills/ncreighton/ai-community-toxic-comment-classifier

---


# AI Community Toxic Comment Classifier & Response Recommendation Engine

## Overview

This production-ready skill automates community moderation by analyzing user comments, classifying toxicity types, calculating severity scores (0-100), and recommending tailored response strategies. Unlike basic keyword filters, this AI-powered system understands context, intent, and nuance—distinguishing between spam, hate speech, misinformation, bad faith criticism, and legitimate concerns.

**Why it matters:** Community managers spend 15-20 hours/week on moderation. This skill reduces that to minutes while improving consistency and response quality. It integrates seamlessly with **WordPress (WP REST API)**, **Discord (Bot API)**, **Slack (incoming webhooks)**, **Google Sheets (append-only audit logs)**, and custom platforms via JSON webhooks.

**Key value propositions:**
- Reduces moderation response time by 85%
- Provides consistent, templated responses aligned with your community values
- Creates audit trails for compliance (GDPR, platform policies)
- Learns from your specific community guidelines over time
- Prevents escalation through intelligent triage (delete vs. respond vs. DM)

---

## Quick Start

Try these prompts immediately to see the skill in action:

### Example 1: Basic Toxicity Analysis
```
Analyze this comment for toxicity:
"Your product is garbage and anyone who buys it is an idiot. 
This company is a scam and should be shut down."
```

**Expected output:** Severity 78/100, Type: Hate Speech + Bad Faith Criticism, 
Recommended action: Respond publicly with empathy template, offer refund/support.

### Example 2: Batch Processing with Slack Integration
```
Process these 5 comments and send moderation summary to Slack webhook:

1. "This feature request is stupid lol"
2. "I love your product! Just a small bug with the API docs"
3. "BUY CRYPTO NOW!!! CLICK LINK!!!"
4. "Your competitor's product is better because of X, Y, Z"
5. "Kill all [group]. This product enables genocide."

Webhook URL: https://hooks.slack.com/services/YOUR/WEBHOOK/URL
Channel: #moderation-queue
```

### Example 3: WordPress Integration with Audit Trail
```
Fetch pending comments from WordPress site:
URL: https://mysite.com
API credentials: (use env var WORDPRESS_API_TOKEN)

Classify each comment. For severity >= 70:
- Flag for manual review
- Log to Google Sheet: https://docs.google.com/spreadsheets/d/SHEET_ID
- Send DM template to comment author
- Recommend deletion with reason code
```

### Example 4: Learning from Community Guidelines
```
Upload my community guidelines PDF and learn response patterns:
File: community-guidelines.pdf

Then classify this comment using those learned patterns:
"This is off-topic but I wanted to share my political views..."
```

---

## Capabilities

### 1. **Multi-Type Toxicity Classification**
The skill categorizes comments into these types (multiple can apply):
- **Spam:** Promotional links, bot-generated content, repetitive messages
- **Hate Speech:** Dehumanizing language, slurs, calls for violence against groups
- **Misinformation:** False factual claims, conspiracy theories, dangerous health advice
- **Bad Faith Criticism:** Attacks on character vs. ideas, strawmanning, bad-faith arguments
- **Legitimate Criticism:** Valid concerns, feature requests, bug reports (marked as non-toxic)
- **Off-Topic:** Content outside community scope (low priority)
- **Sarcasm/Dark Humor:** Context-aware detection to avoid false positives

**Usage example:**
```
Classify with detailed reasoning:
"Vaccines cause autism and the government is hiding the truth!"

Include:
- Primary type
- Secondary types (if any)
- Confidence score per type
- Specific phrases triggering classification
```

### 2. **Severity Scoring (0-100 Scale)**
Dynamic scoring based on:
- Toxicity intensity (language, tone, intent)
- Community impact (targeting vulnerable groups, encouraging action)
- Context (first offense vs. repeat offender)
- Scope (individual attack vs. systemic claim)

**Example:**
```
Score severity for:
"You're wrong about X" → 5/100 (legitimate disagreement)
"You're an idiot" → 25/100 (personal attack, low impact)
"[Slur] should be killed" → 95/100 (hate speech, calls for violence)
```

### 3. **Intelligent Response Recommendation Engine**
Suggests actions with templated responses:

| Severity | Recommended Action | Template Type |
|----------|-------------------|---------------|
| 0-20 | Approve & highlight | Supportive reply |
| 21-50 | Respond publicly | Empathy + boundary-setting |
| 51-75 | DM privately + monitor | Coaching + warning |
| 76-100 | Delete + DM reason | Firm boundary + resources |

**Example output:**
```
Action: RESPOND_PUBLICLY
Template: "Thanks for your feedback. We understand your frustration. 
Here's how we address [concern]. If you'd like to discuss further, 
please DM us or email support@..."

Alternative templates:
- Empathetic (acknowledge emotion first)
- Firm (clear boundary)
- Educational (provide resources)
- Redirect (move to appropriate channel)
```

### 4. **Integration Connectors**
- **WordPress:** Fetch pending comments, auto-approve/trash, reply via REST API
- **Discord:** Analyze messages, flag in mod-queue channel, soft-delete with DM
- **Slack:** Send moderation summaries, approve/reject from thread
- **Google Sheets:** Append audit logs with timestamp, comment text, classification, action taken
- **Webhooks:** POST classification results to custom platforms (Discourse, Mighty Networks, etc.)

### 5. **Adaptive Learning**
- Upload community guidelines, values statements, or past moderation decisions
- Skill learns your specific tone, thresholds, and response patterns
- Improves classification accuracy over time (within single session)
- Generates "moderation playbook" recommendations

**Usage:**
```
Learn from my moderation history:
- Google Sheet with 200 past decisions: https://docs.google.com/spreadsheets/d/ID
- Community guidelines PDF
- Tone guide (formal vs. casual)

Then re-classify these 10 comments using learned patterns.
```

### 6. **Audit Trail & Compliance**
- Logs every classification decision with reasoning
- Exports compliance-ready reports (GDPR, platform policy adherence)
- Timestamps all actions
- Tracks decision consistency over time

---

## Configuration

### Environment Variables (Required)
```bash
# OpenAI API for classification intelligence
OPENAI_API_KEY=sk-...

# Optional: Slack webhook for real-time moderation alerts
SLACK_WEBHOOK_URL=https://hooks.slack.com/services/...

# Optional: WordPress REST API credentials
WORDPRESS_API_TOKEN=your_token_here
WORDPRESS_SITE_URL=https://yoursite.com

# Optional: Google Sheets API for audit logs
GOOGLE_SHEETS_API_KEY=your_key_here
GOOGLE_SHEET_ID=sheet_id_here
```

### Skill Options
```
--severity-threshold=50        # Only flag comments above this score
--batch-size=20                # Process up to 20 comments per run
--language=en                  # Supports: en, es, fr, de, zh, ja
--learning-mode=true           # Enable adaptive learning from guidelines
--audit-log=true               # Enable Google Sheets logging
--dry-run=false                # Set true to preview without taking action
--response-template-set=professional  # Options: professional, casual, firm, empathetic
```

### Setup Steps
1. **Get API Keys:**
   - OpenAI: https://platform.openai.com/api-keys
   - Slack: Create incoming webhook in workspace settings
   - WordPress: Generate application password in user settings
   - Google Sheets: Enable API and create service account

2. **Set Environment Variables:**
   ```bash
   export OPENAI_API_KEY=sk-...
   export SLACK_WEBHOOK_URL=https://hooks.slack.com/...
   ```

3. **Test Integration:**
   ```
   Test WordPress connection:
   site_url: https://mysite.com
   api_token: (from env)
   Expected: Returns 5 pending comments
   ```

4. **(Optional) Upload Community Guidelines:**
   - PDF, Google Doc, or plain text
   - Skill extracts values and moderation patterns
   - Uses for context in future classifications

---

## Example Outputs

### Single Comment Classification
```json
{
  "comment_id": "12345",
  "text": "This product is terrible and you should all switch to [competitor]",
  "author": "john_doe",
  "timestamp": "2024-01-15T14:32:00Z",
  "classification": {
    "primary_type": "bad_faith_criticism",
    "secondary_types": ["legitimate_criticism"],
    "severity_score": 42,
    "confidence": 0.89,
    "reasoning": "Contains legitimate product comparison but frames it as absolute judgment without constructive feedback"
  },
  "recommended_action": "RESPOND_PUBLICLY",
  "response_template": "empathy_plus_redirect",
  "suggested_response": "We appreciate you sharing your experience! We'd love to understand what specific features are missing for you. Can you tell us more about your use case? Our support team at support@... can also discuss alternatives.",
  "alternative_actions": ["APPROVE_AND_HIGHLIGHT", "DM_PRIVATELY"],
  "learning_notes": "Similar to past decision #89. User shows pattern of comparison criticism. Consider monitoring for repeat offense."
}
```

### Batch Processing Summary
```
Moderation Report: 2024-01-15
Total comments processed: 47
Distribution:
  Approved (0-20): 28 comments
  Monitor (21-50): 12 comments
  Review (51-75): 5 comments
  Delete (76-100): 2 comments

High-priority items:
  - Comment #445 (Severity 89): Hate speech + calls for violence
    Action: DELETE + DM author with resources
  - Comment #312 (Severity 76): Misinformation about safety
    Action: RESPOND_PUBLICLY + add fact-check link

Patterns detected:
  - 3 spam comments from same IP (recommend IP ban)
  - Misinformation cluster around COVID (10 comments)
  - Legitimate feature requests (8 comments, highlight for product team)

Audit trail: https://docs.google.com/spreadsheets/d/SHEET_ID
Slack summary: Posted to #moderation-queue
```

### Slack Integration Output
```
🛡️ Moderation Alert (2024-01-15 14:35 UTC)

⚠️ HIGH PRIORITY (Severity 87/100)
Comment ID: #445 | Author: @toxic_user
Type: Hate Speech + Calls for Violence
Text: "[Slur] should be... [REDACTED]"
Recommended: DELETE + DM with resources
Action buttons: [Delete] [Respond] [Defer to Mod] [Learn from this]

📊 Daily Summary
47 comments | 28 approved | 12 flagged | 5 under review | 2 deleted
Consistency score: 94% (vs. past moderation)
```

---

## Tips & Best Practices

### 1. **Start with Dry-Run Mode**
```
Run with --dry-run=true for first 100 comments
Review recommendations before enabling auto-actions
Adjust severity thresholds based on false positive rate
```

### 2. **Upload Community Guidelines Early**
- Skill learns your specific values and tone
- Classification accuracy improves 15-25% with guidelines
- Update guidelines quarterly as community evolves
- Include examples of approved vs. rejected comments

### 3. **Use Response Templates Strategically**
- **Professional tone:** B2B communities, formal support
- **Casual tone:** Gaming, hobby communities, Discord
- **Firm tone:** Zero-tolerance policies, safety-critical
- **Empathetic tone:** Mental health, support communities
- Mix templates: Use firm + empathetic for serious violations

### 4. **Monitor False Positives Weekly**
```
Check audit log for:
- Sarcasm flagged as hate speech
- Legitimate criticism marked as bad faith
- Off-topic marked as spam (when relevant)

Adjust learning model based on 5+ false positives of same type
```

### 5. **Integrate with Moderation Workflow**
- Severity 76-100: Auto-delete (with audit trail)
- Severity 51-75: Send to #moderation-queue in Slack (human review)
- Severity 21-50: Auto-respond with template (human can edit before sending)
- Severity 0-20: Auto-approve (human can override)

### 6. **Track Repeat Offenders**
- Skill identifies users with 3+ violations
- Recommend escalating action (DM warning → temporary mute → ban)
- Export repeat offender list monthly for pattern analysis

### 7. **A/B Test Response Templates**
- Track engagement rate on different template types
- Monitor if firm responses reduce repeat violations
- Adjust based on community response

---

## Safety & Guardrails

### What This Skill Will NOT Do
- **Not a legal tool:** Does not replace legal review for compliance (GDPR, CCPA, etc.). Always consult legal counsel.
- **Not a judge:** Recommendations are suggestions, not final decisions. Humans retain full authority.
- **Not bias-free:** AI models reflect training data biases. Regularly audit for disparate impact across user groups.
- **Not a surveillance tool:** Should not be used to monitor employees, private messages, or non-public content without consent.
- **Not for harassment:** Cannot be weaponized to target individuals or groups. Skill will refuse requests that appear retaliatory.

### Boundaries & Limitations
1. **Context loss:** May misclassify sarcasm, idioms, or cultural references (especially non-English)
2. **Evolving slurs:** Cannot catch novel slurs or coded language (requires human review for edge cases)
3. **False positives on satire:** May flag legitimate satire as hate speech (review before deletion)
4. **No private data learning:** Skill does not learn from deleted comments or private messages
5. **Rate limits:** OpenAI API has rate limits (100 requests/min on free tier; higher on paid)
6. **Language support:** Best accuracy in English; moderate accuracy in Spanish, French, German; lower in others

### Ethical Guidelines
- **Transparency:** Inform community members that AI moderation is in use
- **Appeal process:** Always allow users to appeal classifications (provide support email)
- **No shadow banning:** Don't use skill to silently suppress comments without user knowledge
- **Diverse moderation team:** Don't rely solely on AI; pair with human moderators from diverse backgrounds
- **Regular audits:** Monthly review of classification patterns for bias (by demographic, topic, etc.)

### Compliance Notes
- **GDPR:** Audit logs include personal data; ensure retention policy complies (delete after 90 days if not needed)
- **Platform policies:** Verify skill's actions comply with WordPress, Discord, Slack ToS
- **Defamation risk:** Ensure response templates don't make false claims about users
- **Accessibility:** Ensure Slack/email notifications are accessible (alt text for images, captions for videos)

---

## Troubleshooting

### Common Issues & Solutions

**Q: Skill is classifying legitimate criticism as "bad faith"**
- A: Upload community guidelines with examples of good vs. bad criticism. Adjust `--severity-threshold` lower. Review the "reasoning" field in output to understand the decision.

**Q: False positives on sarcasm (e.g., "Great job breaking the site again!")**
- A: Sarcasm is context-dependent. Skill has lower confidence on sarcasm (check `confidence` field). For communities heavy in sarcasm, use `--response-template-set=casual` and manually