| name | adverse-media |
| description | Search for negative news coverage, controversies, and reputational risks associated with individuals or companies across news sources and media databases |
| allowed-tools | ["Bash","Read","Write","WebSearch"] |
Adverse Media Screening Skill
Purpose
This skill searches for negative news, controversies, scandals, and reputational risks associated with entities across global news sources and media databases.
When to Use This Skill
Activate this skill when the user:
- Requests adverse media or negative news screening
- Asks about controversies or scandals involving an entity
- Needs reputational risk assessment
- Wants to check media coverage of a person or company
- Uses keywords like: "adverse media", "negative news", "scandals", "controversies", "bad press"
How to Use
1. Identify Search Target
- Extract entity name
- Note time period if specified
- Consider name variations and aliases
2. Run Adverse Media Search
cd /Users/superfunguy/wsp/scolo/backend
python -c "from src.tools import adverse_media; import json; result = adverse_media.check('ENTITY_NAME'); print(json.dumps(result, indent=2))"
3. Analyze Results
Categories of adverse media:
- Financial Crime: Fraud, money laundering, embezzlement
- Corruption: Bribery, kickbacks, political corruption
- Legal Issues: Lawsuits, regulatory violations, arrests
- Ethical Concerns: Environmental damage, labor violations
- Reputational: Scandals, controversies, negative publicity
Examples
Example: Check Company Reputation
User: "Any negative news about Wells Fargo?"
Action:
python -c "from src.tools import adverse_media; import json; result = adverse_media.check('Wells Fargo'); print(json.dumps(result, indent=2))"
Important Notes
- Consider source credibility and bias
- Distinguish between allegations and confirmed facts
- Check publication dates for relevance
- Multiple sources strengthen findings
