Module: ContentGeneration/BreakingNews

INTELLIGENCE OPERATIVE PERSPECTIVE

This module generates breaking news articles for significant parliamentary events, operating as the real-time intelligence alert layer of the platform. Breaking news covers voting surprises, unexpected statements, coalition developments, and crisis situations that demand immediate notification to stakeholders. In intelligence operations, breaking news serves the critical function of alerting analysts to developments that may change strategic assessments.

ARTICLE SCOPE & TRIGGERS: Breaking news articles are generated when:

• Unexpected or significant parliamentary votes occur
• Surprise announcements from government or opposition
• Coalition realignment or party conflict erupts
• Procedural surprises or rule violations
• International incident affects Swedish politics
• Crisis response requiring immediate parliamentary action

CONTENT STRUCTURE: Each breaking news article follows a standardized intelligence format:

1. What Happened: Factual description of event in first 100 words
2. Why It Matters: Political implications and stakeholder impact
3. Party Reactions: Documented positions from major parties
4. Coalition Impact: How development affects government stability
5. Next Steps: Predicted follow-up actions or timeline

MCP DATA SOURCES: Required tools for article validation (validation layer):

• search_voteringar: Vote records for parliamentary actions
• get_voting_group: Group voting patterns showing party consensus/splits
• search_anforanden: Member speeches providing context and reactions
• search_ledamoter: Member information for quote attribution

IMPLEMENTATION STATUS:

• Actual implementation calls: search_voteringar, search_anforanden
• TODO implementation: get_voting_group, search_ledamoter Note: This causes validation warnings but allows tests to pass. Full implementation should complete all four tool integrations.

INTELLIGENCE ANALYSIS FRAMEWORK: Breaking news articles incorporate:

• Vote tallies showing coalition positions
• Historical voting pattern changes (anomaly detection)
• Statement analysis from parliamentary speeches
• Member career progression (political weight analysis)
• Timeline reconstruction of surprising developments

LANGUAGE SUPPORT (14 Languages):

• Swedish (SV): Source language, immediate publication
• English (EN): Primary international audience
• Nordic (DA, NO, FI): Regional distribution
• European (DE, FR, ES, NL): Continental coverage
• Middle Eastern (AR, HE): Diplomatic audience
• Asian (JA, KO, ZH): Economic audience

OPERATIONAL WORKFLOW:

1. Event Detection: Monitor voting patterns for anomalies
2. Context Gathering: Retrieve vote details, speeches, member info
3. Analysis: Assess political significance and implications
4. Article Generation: Create structure with MCP data citations
5. Translation: Generate non-Swedish language versions
6. Publication: Deploy to news directory with metadata

TIMING CONSIDERATIONS:

• Trigger: Within 15 minutes of vote conclusion
• Generation: 5-10 minutes including MCP calls and translation
• Publication: Immediate upon completion (no editorial delay)
• Update Cycle: Revisits article if new votes/statements within 1 hour

INTELLIGENCE QUALITY METRICS:

• Quote Count: Minimum 3+ party perspectives represented
• Source Density: At least 4 distinct MCP tool calls
• Temporal Accuracy: Timestamp synchronization with actual vote
• Political Neutrality: Balanced presentation across ideological spectrum

RISK ASSESSMENT INTEGRATION: Breaking news articles feed into risk assessment models:

• Coalition Stability: Changes in government support indicators
• Political Volatility: Frequency and magnitude of unexpected votes
• Member Realignment: Crossing party lines signals cooperation changes
• Crisis Indicators: Sudden procedural or security-related developments

MULTILINGUAL CONTENT CHALLENGES:

• Idiom Translation: Political terminology varies across languages
• Cultural Context: Swedish political references need international explanation
• Urgency Signaling: Different languages emphasize breaking news differently
• Member Names: Proper name formatting rules vary by target language

PERFORMANCE OPTIMIZATION:

• MCP Query Caching: 2-hour cache for frequently-requested data
• Parallel Translation: All 14 languages generated simultaneously
• Incremental Parsing: Stream vote data to prevent full loads
• Smart Updates: Only regenerate articles with new/changed data

FAILURE SCENARIOS:

• MCP Service Down: Graceful degradation with cached data
• Translation Failure: Fall back to machine translation + manual review queue
• Missing Member Data: Generate article with available quotes
• Parsing Error: Alert editorial team, skip problematic article

GDPR COMPLIANCE:

• Member quotes sourced to specific votes (transparency)
• Personal data handling follows DPA requirements
• Data retention integrated with article archive policy
• Member consent tracking for non-public statements