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* @module pre-article-analysis/markdown-serializer
* @description Serializes analysis framework results as structured markdown
* files for persistence in `analysis/daily/YYYY-MM-DD/`.
*
* Each output file follows the standard analysis template:
* ```markdown
* # [Analysis Type] — YYYY-MM-DD
* **Generated**: YYYY-MM-DD HH:MM UTC
* **Data Sources**: [list]
* **Documents Analyzed**: N
* **Confidence**: HIGH/MEDIUM/LOW
* ## Summary / ## Detailed Analysis / ## Key Findings / ## Implications
* ```
*
* @author Hack23 AB
* @license Apache-2.0
*/
import type {
DocumentAnalysisResult,
PerspectiveAnalysis,
DocumentLink,
} from '../analysis-framework/types.js';
// ---------------------------------------------------------------------------
// Types
// ---------------------------------------------------------------------------
export interface SerializationContext {
/** ISO date string, e.g. "2026-03-26" */
date: string;
/** UTC timestamp of generation */
generatedAt: string;
/** List of MCP tool names called to download data */
dataSources: string[];
}
export interface SignificanceEntry {
dok_id: string;
title: string;
score: number;
doctype: string;
}
export interface RiskAssessmentResult {
coalitionRiskScore: number;
riskLevel: 'LOW' | 'MEDIUM' | 'HIGH' | 'CRITICAL';
riskSummary: string;
anomalyFlags: Array<{ type: string; severity: string; description: string }>;
implications: string[];
}
export interface SwotSummary {
strengths: string[];
weaknesses: string[];
opportunities: string[];
threats: string[];
forStakeholder: string;
}
export interface CrossReferenceSummary {
docCount: number;
totalLinks: number;
links: DocumentLink[];
}
export interface SynthesisSummary {
totalDocs: number;
executiveSummary: string;
keyFindings: string[];
topDocuments: SignificanceEntry[];
overallConfidence: 'HIGH' | 'MEDIUM' | 'LOW';
aggregateRiskLevel: string;
}
// ---------------------------------------------------------------------------
// Helpers
// ---------------------------------------------------------------------------
/**
* Map a numeric confidence score (0–100) to a categorical label.
* - ≥70: HIGH — strong evidence, full-text content available for most documents
* - 40–69: MEDIUM — moderate evidence, mix of full-text and metadata-only
* - <40: LOW — weak evidence, metadata-only documents or small batch
*/
function confidenceLabel(score: number): 'HIGH' | 'MEDIUM' | 'LOW' {
if (score >= 70) return 'HIGH';
if (score >= 40) return 'MEDIUM';
return 'LOW';
}
/** Maximum number of documents shown in the detailed analysis section */
const MAX_DETAILED_RESULTS = 20;
function significanceLabel(score: number): string {
if (score >= 8) return '🔴 Critical';
if (score >= 6) return '🟠 High';
Iif (score >= 4) return '🟡 Medium';
return '🟢 Low';
}
function escapeMarkdownTableCell(value: string): string {
return value
.replace(/\\/g, '\\\\')
.replace(/\r?\n/g, ' ')
.replace(/\|/g, '\\|')
.trim();
}
function frontmatter(ctx: SerializationContext, title: string, docCount: number, confidenceScore: number): string {
return [
`# ${title} — ${ctx.date}`,
'',
`**Generated**: ${ctx.generatedAt}`,
`**Data Sources**: ${ctx.dataSources.join(', ')}`,
`**Documents Analyzed**: ${docCount}`,
`**Confidence**: ${confidenceLabel(confidenceScore)}`,
'',
].join('\n');
}
// ---------------------------------------------------------------------------
// Data-download manifest
// ---------------------------------------------------------------------------
export function serializeDataManifest(
ctx: SerializationContext,
docCounts: Record<string, number>,
dateFilteredTotal?: number,
): string {
const totalDocs = Object.values(docCounts).reduce((a, b) => a + b, 0);
const analyzedCount = dateFilteredTotal ?? totalDocs;
const lines: string[] = [
frontmatter(ctx, 'Data Download Manifest', analyzedCount, 100),
'## Summary',
'',
`Downloaded **${totalDocs}** documents (session-wide) from ${ctx.dataSources.length} MCP data sources.`,
'',
];
if (dateFilteredTotal !== undefined) {
lines.push(`After date filtering to **${ctx.date}**: **${dateFilteredTotal}** documents selected for analysis.`, '');
}
lines.push('## Document Counts by Type', '');
for (const [type, count] of Object.entries(docCounts)) {
lines.push(`- **${type}**: ${count} documents`);
}
lines.push('', '## Data Quality Notes', '', 'All documents sourced from official riksdag-regering-mcp API.');
return lines.join('\n');
}
// ---------------------------------------------------------------------------
// Classification results
// ---------------------------------------------------------------------------
export function serializeClassificationResults(
ctx: SerializationContext,
results: DocumentAnalysisResult[],
): string {
const avgConfidence =
results.length > 0
? results.reduce((sum, r) => sum + r.confidenceScore, 0) / results.length
: 0;
const lines: string[] = [
frontmatter(ctx, 'Political Classification Results', results.length, avgConfidence),
'## Summary',
'',
`Classified **${results.length}** parliamentary documents by sensitivity, impact, urgency, and domain.`,
'',
'## Detailed Analysis',
'',
];
for (const result of results.slice(0, MAX_DETAILED_RESULTS)) {
const title = result.document.titel || result.document.title || result.document.dok_id || 'Unknown';
const dokId = result.document.dok_id || 'N/A';
const domains = result.perspectives
.flatMap(p => p.relatedPolicies)
.filter((v, i, arr) => arr.indexOf(v) === i)
.slice(0, 3);
lines.push(`### ${title}`);
lines.push(`- **dok_id**: ${dokId}`);
lines.push(`- **Type**: ${result.document.doktyp || 'unknown'}`);
lines.push(`- **Significance**: ${significanceLabel(result.overallSignificance)} (${result.overallSignificance}/10)`);
lines.push(`- **Domains**: ${domains.join(', ') || 'General'}`);
lines.push(`- **Confidence**: ${confidenceLabel(result.confidenceScore)} (${Math.round(result.confidenceScore)}%)`);
lines.push('');
}
lines.push('## Key Findings', '');
const topDocs = [...results].sort((a, b) => b.overallSignificance - a.overallSignificance).slice(0, 5);
topDocs.forEach((r, i) => {
const title = r.document.titel || r.document.title || r.document.dok_id || 'Unknown';
lines.push(`${i + 1}. **${title}** (dok_id: ${r.document.dok_id || 'N/A'}) — Significance: ${r.overallSignificance}/10`);
});
lines.push('', '## Implications', '');
lines.push('Classification drives article prioritisation. High-significance documents should receive deep-inspection treatment.');
lines.push('', '## Data Quality Notes', '');
lines.push(`Classification confidence: ${confidenceLabel(avgConfidence)}. Higher confidence when full-text content is available.`);
return lines.join('\n');
}
// ---------------------------------------------------------------------------
// Risk assessment
// ---------------------------------------------------------------------------
export function serializeRiskAssessment(
ctx: SerializationContext,
docCount: number,
risk: RiskAssessmentResult,
): string {
const confidenceScore = risk.riskLevel === 'LOW' ? 80 : risk.riskLevel === 'MEDIUM' ? 60 : 40;
const lines: string[] = [
frontmatter(ctx, 'Political Risk Assessment', docCount, confidenceScore),
'## Summary',
'',
risk.riskSummary,
'',
'## Detailed Analysis',
'',
`**Coalition Risk Score**: ${risk.coalitionRiskScore}/100`,
`**Risk Level**: ${risk.riskLevel}`,
'',
'### Anomaly Flags',
'',
];
if (risk.anomalyFlags.length > 0) {
for (const flag of risk.anomalyFlags) {
lines.push(`- **[${flag.severity}]** ${flag.type}: ${flag.description}`);
}
} else {
lines.push('No anomalous patterns detected in current data.');
}
lines.push('', '## Key Findings', '');
lines.push(`1. Coalition stability at risk score **${risk.coalitionRiskScore}** (${risk.riskLevel})`);
if (risk.anomalyFlags.length > 0) {
lines.push(`2. **${risk.anomalyFlags.length}** anomaly flag(s) detected requiring monitoring`);
}
lines.push('', '## Implications', '');
for (const impl of risk.implications) {
lines.push(`- ${impl}`);
}
lines.push('', '## Data Quality Notes', '');
lines.push('Risk assessment derived from CIA coalition metrics and document significance scores.');
return lines.join('\n');
}
// ---------------------------------------------------------------------------
// SWOT analysis
// ---------------------------------------------------------------------------
export function serializeSwotAnalysis(
ctx: SerializationContext,
docCount: number,
swots: SwotSummary[],
): string {
const lines: string[] = [
frontmatter(ctx, 'Political SWOT Analysis', docCount, 70),
'## Summary',
'',
`Generated SWOT analysis for **${swots.length}** political actor(s) based on ${docCount} documents.`,
'',
'## Detailed Analysis',
'',
];
for (const swot of swots) {
lines.push(`### ${swot.forStakeholder}`, '');
lines.push('**Strengths**');
swot.strengths.forEach(s => lines.push(`- ${s}`));
lines.push('');
lines.push('**Weaknesses**');
swot.weaknesses.forEach(s => lines.push(`- ${s}`));
lines.push('');
lines.push('**Opportunities**');
swot.opportunities.forEach(s => lines.push(`- ${s}`));
lines.push('');
lines.push('**Threats**');
swot.threats.forEach(s => lines.push(`- ${s}`));
lines.push('');
}
lines.push('## Key Findings', '');
lines.push('1. SWOT entries derived from all six perspective analyses across downloaded documents.');
lines.push('', '## Implications', '');
lines.push('SWOT insights should inform stakeholder framing in generated articles.');
lines.push('', '## Data Quality Notes', '');
lines.push('SWOT confidence is proportional to document richness (full-text vs metadata-only).');
return lines.join('\n');
}
// ---------------------------------------------------------------------------
// Threat analysis
// ---------------------------------------------------------------------------
export function serializeThreatAnalysis(
ctx: SerializationContext,
results: DocumentAnalysisResult[],
): string {
const threatEntries = results.flatMap(r =>
r.perspectives.flatMap(p =>
p.swotContribution
.filter(c => c.quadrant === 'threat')
.map(c => ({ title: r.document.titel || r.document.title || r.document.dok_id || 'Unknown', text: c.text, forStakeholder: c.forStakeholder }))
)
);
const avgConfidence =
results.length > 0
? results.reduce((sum, r) => sum + r.confidenceScore, 0) / results.length
: 0;
const lines: string[] = [
frontmatter(ctx, 'Political Threat Analysis', results.length, avgConfidence),
'## Summary',
'',
`Identified **${threatEntries.length}** threat indicators across ${results.length} documents.`,
'',
'## Detailed Analysis',
'',
];
const grouped = new Map<string, string[]>();
for (const entry of threatEntries) {
const arr = grouped.get(entry.forStakeholder) ?? [];
arr.push(`[${entry.title}] ${entry.text}`);
grouped.set(entry.forStakeholder, arr);
}
for (const [stakeholder, threats] of grouped) {
lines.push(`### Threats for: ${stakeholder}`, '');
threats.slice(0, 5).forEach(t => lines.push(`- ${t}`));
lines.push('');
}
lines.push('## Key Findings', '');
lines.push(`1. **${threatEntries.length}** threat indicators identified targeting ${grouped.size} stakeholder group(s)`);
lines.push('', '## Implications', '');
lines.push('Threat analysis should inform risk-focused article framing and editorial prioritisation.');
lines.push('', '## Data Quality Notes', '');
lines.push(`Analysis confidence: ${confidenceLabel(avgConfidence)}.`);
return lines.join('\n');
}
// ---------------------------------------------------------------------------
// Stakeholder perspectives
// ---------------------------------------------------------------------------
export function serializeStakeholderPerspectives(
ctx: SerializationContext,
results: DocumentAnalysisResult[],
): string {
const avgConfidence =
results.length > 0
? results.reduce((sum, r) => sum + r.confidenceScore, 0) / results.length
: 0;
// Aggregate perspectives by lens across all documents
const lensMap = new Map<string, PerspectiveAnalysis[]>();
for (const result of results) {
for (const p of result.perspectives) {
const arr = lensMap.get(p.lens) ?? [];
arr.push(p);
lensMap.set(p.lens, arr);
}
}
const lines: string[] = [
frontmatter(ctx, 'Stakeholder Perspective Analysis', results.length, avgConfidence),
'## Summary',
'',
`Applied **6 analysis lenses** to **${results.length}** documents.`,
'',
'## Detailed Analysis',
'',
];
const lensEmoji: Record<string, string> = {
government: '🏛️',
opposition: '⚖️',
citizen: '👥',
economic: '💰',
international: '🌍',
media: '📰',
};
for (const [lens, perspectives] of lensMap) {
const emoji = lensEmoji[lens] || '🔍';
const high = perspectives.filter(p => p.impact === 'high').length;
const avgConf = perspectives.reduce((s, p) => s + p.confidence, 0) / perspectives.length;
const topActors = [...new Set(perspectives.flatMap(p => p.keyActors))].slice(0, 5);
lines.push(`### ${emoji} ${lens.charAt(0).toUpperCase() + lens.slice(1)} Perspective`, '');
lines.push(`- **Documents with High Impact**: ${high}/${perspectives.length}`);
lines.push(`- **Avg Confidence**: ${Math.round(avgConf)}%`);
lines.push(`- **Key Actors**: ${topActors.join(', ') || 'N/A'}`);
lines.push('');
// Show top 3 summaries
const topThree = [...perspectives].sort((a, b) => b.confidence - a.confidence).slice(0, 3);
for (const p of topThree) {
Eif (p.summary) {
lines.push(`> ${p.summary}`);
lines.push('');
}
}
}
lines.push('## Key Findings', '');
lines.push('1. All six stakeholder perspectives applied consistently across the document batch.');
lines.push('2. Cross-perspective conflicts indicate politically contentious documents.');
lines.push('', '## Implications', '');
lines.push('Perspective analysis feeds directly into article stakeholder framing and balance.');
lines.push('', '## Data Quality Notes', '');
lines.push(`Aggregate confidence: ${confidenceLabel(avgConfidence)}.`);
return lines.join('\n');
}
// ---------------------------------------------------------------------------
// Significance scoring
// ---------------------------------------------------------------------------
export function serializeSignificanceScoring(
ctx: SerializationContext,
entries: SignificanceEntry[],
): string {
const lines: string[] = [
frontmatter(ctx, 'Document Significance Scoring', entries.length, 80),
'## Summary',
'',
`Scored **${entries.length}** documents for political significance (0–10 scale).`,
'',
'## Detailed Analysis',
'',
'| Score | Level | Type | dok_id | Title |',
'|-------|-------|------|--------|-------|',
];
const sorted = [...entries].sort((a, b) => b.score - a.score);
for (const entry of sorted.slice(0, 30)) {
const level = escapeMarkdownTableCell(significanceLabel(entry.score).replace(/🔴|🟠|🟡|🟢/g, '').trim());
const titleValue = entry.title.length > 50 ? entry.title.slice(0, 47) + '...' : entry.title;
const doctype = escapeMarkdownTableCell(entry.doctype);
const dokId = escapeMarkdownTableCell(entry.dok_id);
const title = escapeMarkdownTableCell(titleValue);
lines.push(`| ${entry.score}/10 | ${level} | ${doctype} | ${dokId} | ${title} |`);
}
lines.push('', '## Key Findings', '');
const critical = sorted.filter(e => e.score >= 8);
lines.push(`1. **${critical.length}** document(s) rated Critical (score ≥ 8)`);
const high = sorted.filter(e => e.score >= 6 && e.score < 8);
lines.push(`2. **${high.length}** document(s) rated High (score 6–7)`);
lines.push('', '## Implications', '');
lines.push('High-significance documents should be prioritised for deep-inspection article generation.');
lines.push('', '## Data Quality Notes', '');
lines.push('Significance scores use document type, committee tier, domain breadth, coalition context, and content richness.');
return lines.join('\n');
}
// ---------------------------------------------------------------------------
// Cross-reference map
// ---------------------------------------------------------------------------
export function serializeCrossReferenceMap(
ctx: SerializationContext,
summary: CrossReferenceSummary,
): string {
const lines: string[] = [
frontmatter(ctx, 'Cross-Reference Map', summary.docCount, 75),
'## Summary',
'',
`Detected **${summary.totalLinks}** cross-document relationships.`,
'',
'## Detailed Analysis',
'',
];
if (summary.links.length === 0) {
lines.push('No cross-document relationships detected in current batch.');
} else {
const byType = new Map<string, DocumentLink[]>();
for (const link of summary.links) {
const arr = byType.get(link.type) ?? [];
arr.push(link);
byType.set(link.type, arr);
}
for (const [type, links] of byType) {
lines.push(`### ${type}`, '');
for (const link of links.slice(0, 10)) {
lines.push(`- **${link.sourceId}** → **${link.targetId}** (confidence: ${link.confidence}%)`);
lines.push(` _${link.reason}_`);
}
lines.push('');
}
}
lines.push('## Key Findings', '');
lines.push(`1. **${summary.totalLinks}** inter-document relationships mapped`);
lines.push('', '## Implications', '');
lines.push('Cross-references enrich article narratives by linking related legislative developments.');
lines.push('', '## Data Quality Notes', '');
lines.push('Cross-reference confidence is driven by shared policy domains and textual similarity.');
return lines.join('\n');
}
// ---------------------------------------------------------------------------
// Synthesis summary
// ---------------------------------------------------------------------------
export function serializeSynthesisSummary(
ctx: SerializationContext,
synthesis: SynthesisSummary,
): string {
const confScore = synthesis.overallConfidence === 'HIGH' ? 80 : synthesis.overallConfidence === 'MEDIUM' ? 55 : 30;
const lines: string[] = [
frontmatter(ctx, 'Analysis Synthesis Summary', synthesis.totalDocs, confScore),
'## Summary',
'',
synthesis.executiveSummary,
'',
'## Key Findings',
'',
];
synthesis.keyFindings.forEach((f, i) => lines.push(`${i + 1}. ${f}`));
lines.push('', '## Top Documents by Significance', '', '| Score | Type | dok_id | Title |', '|-------|------|--------|-------|');
for (const doc of synthesis.topDocuments.slice(0, 10)) {
const titleValue = doc.title.length > 50 ? doc.title.slice(0, 47) + '...' : doc.title;
const doctype = escapeMarkdownTableCell(doc.doctype);
const dokId = escapeMarkdownTableCell(doc.dok_id);
const title = escapeMarkdownTableCell(titleValue);
lines.push(`| ${doc.score}/10 | ${doctype} | ${dokId} | ${title} |`);
}
lines.push('', '## Implications', '');
lines.push(`Overall political risk level: **${synthesis.aggregateRiskLevel}**`);
lines.push('Articles should reference this synthesis to ensure analytical depth and consistency.');
lines.push('', '## Data Quality Notes', '');
lines.push(`Overall confidence: **${synthesis.overallConfidence}**. All analysis results are available in sibling files.`);
return lines.join('\n');
}
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