Apply comparative politics, political behavior, and policy analysis frameworks to European Parliament data
This skill applies when:
This skill is grounded in the European Parliament MCP Server's access to EP Open Data Portal datasets and aligns with Hack23 ISMS Secure Development Policy for data integrity.
Use the EP MCP Server's plenary vote data to calculate the Agreement Index (AI)
for each political group on environmental legislation in EP10:
- AI = (max(Yes, No, Abstain) - 0.5 * (votes - max(Yes, No, Abstain))) / votes
- Compare cohesion across policy domains (environment vs. economic affairs)
- Identify national delegations that deviate most from group line
- Control for vote salience using roll-call request patterns
Compare Swedish MEP voting patterns across political groups:
- Map Swedish national parties to EP political groups (S → S&D, M → EPP, etc.)
- Calculate loyalty scores: how often Swedish MEPs vote with their group majority
- Identify policy areas where national interest overrides group discipline
- Use MCP Server tools: get_meps (country filter), get_voting_records
Track legislative outcomes through the ordinary legislative procedure:
- Use track_legislation tool to identify dossiers by policy area
- Analyze first-reading agreements vs. second-reading/conciliation outcomes
- Study rapporteur influence: compare committee vote to plenary vote alignment
- Assess EP vs. Council bargaining success rates by policy domain