Best use case
Media Monitoring Skill is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
## Overview
Teams using Media Monitoring Skill should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/cfn-marketing-media-monitoring/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How Media Monitoring Skill Compares
| Feature / Agent | Media Monitoring Skill | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
## Overview
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Media Monitoring Skill
## Overview
Monitor brand mentions across media outlets, analyze sentiment, detect crises, and generate monitoring reports using Meltwater/Brandwatch.
## Operations
### 1. search-mentions.sh
Search for brand mentions across all media sources.
**Parameters**:
- `--query` (required): Search query (brand name, product, executive)
- `--timeframe` (optional): Time range (24h/7d/30d, default: 24h)
- `--sources` (optional): Source types (news/social/blogs/forums, default: all)
- `--limit` (optional): Result limit (default: 50)
**Example**:
```bash
./.claude/skills/cfn-marketing-media-monitoring/operations/search-mentions.sh \
--query "Company Inc" \
--timeframe "24h" \
--sources "news,social"
```
**Response**:
```json
{
"total_mentions": 127,
"mentions": [
{
"id": "mention_123",
"source": "TechCrunch",
"source_type": "news",
"title": "Company Inc Launches New Product",
"url": "https://techcrunch.com/...",
"published_at": "2025-10-29T10:00:00Z",
"sentiment": "positive",
"reach": 500000
}
],
"sentiment_breakdown": {
"positive": 89,
"neutral": 32,
"negative": 6
}
}
```
**Exit Codes**:
- 0: Success
- 1: Invalid parameters
- 2: API error
---
### 2. get-sentiment-analysis.sh
Analyze sentiment of brand mentions.
**Parameters**:
- `--query` (required): Search query
- `--timeframe` (optional): Time range (24h/7d/30d, default: 24h)
- `--breakdown` (optional): Breakdown dimension (source/source_type/date, default: source_type)
**Example**:
```bash
./.claude/skills/cfn-marketing-media-monitoring/operations/get-sentiment-analysis.sh \
--query "Company Inc" \
--timeframe "7d" \
--breakdown "date"
```
**Response**:
```json
{
"query": "Company Inc",
"timeframe": "7d",
"total_mentions": 456,
"overall_sentiment": {
"positive": 72.8,
"neutral": 21.5,
"negative": 5.7
},
"sentiment_by_date": [
{
"date": "2025-10-29",
"positive": 45,
"neutral": 12,
"negative": 3
}
],
"sentiment_trend": "improving",
"crisis_risk": "low"
}
```
**Exit Codes**:
- 0: Success
- 1: Invalid parameters
- 2: API error
---
### 3. create-crisis-alert.sh
Set up crisis detection alert based on sentiment thresholds.
**Parameters**:
- `--query` (required): Search query to monitor
- `--negative-threshold` (optional): Negative sentiment % threshold (default: 50)
- `--positive-threshold` (optional): Positive sentiment % threshold (default: 30)
- `--alert-email` (required): Email for crisis alerts
- `--check-interval` (optional): Check interval in minutes (default: 15)
**Example**:
```bash
./.claude/skills/cfn-marketing-media-monitoring/operations/create-crisis-alert.sh \
--query "Company Inc" \
--negative-threshold 50 \
--positive-threshold 30 \
--alert-email "pr@company.com" \
--check-interval 15
```
**Response**:
```json
{
"alert_id": "alert_xyz789",
"query": "Company Inc",
"status": "active",
"conditions": {
"negative_threshold": 50,
"positive_threshold": 30
},
"alert_email": "pr@company.com",
"check_interval_minutes": 15,
"created_at": "2025-10-29T14:00:00Z"
}
```
**Exit Codes**:
- 0: Success
- 1: Invalid parameters
- 2: API error
- 3: Validation error
**Crisis Detection Requirements**:
- Alert latency: <15 minutes from negative mention
- Crisis response SLA: 2-hour tracking
- Sentiment threshold: <30% positive OR >50% negative
---
### 4. export-report.sh
Export daily/weekly brand mention report.
**Parameters**:
- `--query` (required): Search query
- `--report-type` (required): Report type (daily/weekly/monthly)
- `--format` (optional): Export format (json/csv/pdf, default: json)
- `--email` (optional): Email address to send report
**Example**:
```bash
./.claude/skills/cfn-marketing-media-monitoring/operations/export-report.sh \
--query "Company Inc" \
--report-type "weekly" \
--format "pdf" \
--email "marketing@company.com"
```
**Response**:
```json
{
"report_id": "report_456",
"query": "Company Inc",
"report_type": "weekly",
"format": "pdf",
"period": {
"start": "2025-10-22T00:00:00Z",
"end": "2025-10-29T00:00:00Z"
},
"total_mentions": 456,
"sentiment_summary": {
"positive": 72.8,
"neutral": 21.5,
"negative": 5.7
},
"download_url": "https://reports.example.com/report_456.pdf",
"sent_to": "marketing@company.com"
}
```
**Exit Codes**:
- 0: Success
- 1: Invalid parameters
- 2: API error
## Environment Variables
- `N8N_BASE_URL`: n8n instance URL
- `N8N_API_KEY`: n8n API authentication key
## Integration
All operations use n8n webhooks for Meltwater/Brandwatch integration.Related Skills
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