Add semantic search and analytics tools for sessions
Phase 7 complete: Advanced session analysis capabilities New MCP Tools (3): 1. session_semantic_search - Vector similarity search across all sessions 2. session_productivity_analytics - Metrics (avg duration, tasks, commits, tokens) 3. session_pattern_detection - Detect patterns (tool usage, task types) Features: - Semantic search with embedding-based similarity - Fallback to ILIKE text search if embeddings unavailable - Analytics over configurable time periods (week/month/quarter) - Pattern detection with frequency analysis Use Cases: - Find similar past work: "sessions about WhatsApp integration" - Track productivity: avg commits/tasks per session - Identify tool usage patterns: which tools used most often - Analyze task type distribution All 7 phases complete! System ready for testing. Related: CF-257 Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
This commit is contained in:
Christian Gick
@@ -939,4 +939,39 @@ export const toolDefinitions = [
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required: ['session_id'],
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},
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},
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{
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name: 'session_semantic_search',
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description: 'Semantic search across all session documentation using vector similarity',
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inputSchema: {
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type: 'object',
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properties: {
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query: { type: 'string', description: 'Search query' },
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project: { type: 'string', description: 'Filter by project (optional)' },
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limit: { type: 'number', description: 'Max results (default: 10)' },
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},
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required: ['query'],
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},
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},
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{
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name: 'session_productivity_analytics',
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description: 'Get productivity metrics (avg duration, tasks/commits per session, etc.)',
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inputSchema: {
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type: 'object',
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properties: {
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project: { type: 'string', description: 'Filter by project (optional)' },
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time_period: { type: 'string', enum: ['week', 'month', 'quarter'], description: 'Time period (default: month)' },
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},
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},
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},
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{
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name: 'session_pattern_detection',
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description: 'Detect patterns across sessions (tool usage, task types)',
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inputSchema: {
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type: 'object',
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properties: {
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project: { type: 'string', description: 'Filter by project (optional)' },
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pattern_type: { type: 'string', enum: ['tool_usage', 'task_types', 'error_frequency'], description: 'Type of pattern to detect (default: tool_usage)' },
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},
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},
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},
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];
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@@ -422,3 +422,213 @@ export async function sessionDocumentationGenerate(args: SessionDocumentationGen
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return `Documentation generated for session ${session_id} (${doc.length} characters)`;
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}
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// ============================================================================
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// SEMANTIC SEARCH & ANALYTICS
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// ============================================================================
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interface SessionSemanticSearchArgs {
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query: string;
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project?: string;
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limit?: number;
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}
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interface SessionSearchResult {
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session_id: string;
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session_number: number;
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project: string;
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summary: string | null;
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started_at: string;
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similarity: number;
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}
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/**
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* Semantic search across all session documentation
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* Uses vector similarity to find related sessions
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*/
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export async function sessionSemanticSearch(args: SessionSemanticSearchArgs): Promise<SessionSearchResult[]> {
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const { query: searchQuery, project, limit = 10 } = args;
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// Generate embedding for search query
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const queryEmbedding = await getEmbedding(searchQuery);
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if (!queryEmbedding) {
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// Fallback to text search if embedding generation fails
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let sql = `
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SELECT
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s.id as session_id,
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s.session_number,
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s.project,
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s.summary,
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s.started_at,
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0.5 as similarity
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FROM sessions s
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WHERE s.summary IS NOT NULL
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AND s.status = 'completed'
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${project ? 'AND s.project = $1' : ''}
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AND s.summary ILIKE $${project ? '2' : '1'}
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ORDER BY s.started_at DESC
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LIMIT $${project ? '3' : '2'}
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`;
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const params: unknown[] = project ? [project, `%${searchQuery}%`, limit] : [`%${searchQuery}%`, limit];
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const results = await query<SessionSearchResult>(sql, params);
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return results;
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}
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const embeddingFormatted = formatEmbedding(queryEmbedding);
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// Vector similarity search
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let sql = `
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SELECT
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s.id as session_id,
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s.session_number,
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s.project,
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s.summary,
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s.started_at,
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1 - (s.embedding <=> $1) as similarity
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FROM sessions s
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WHERE s.embedding IS NOT NULL
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${project ? 'AND s.project = $2' : ''}
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AND s.status = 'completed'
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ORDER BY s.embedding <=> $1
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LIMIT $${project ? '3' : '2'}
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`;
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const params: unknown[] = project ? [embeddingFormatted, project, limit] : [embeddingFormatted, limit];
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const results = await query<SessionSearchResult>(sql, params);
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return results;
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}
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interface SessionAnalyticsArgs {
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project?: string;
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time_period?: 'week' | 'month' | 'quarter';
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}
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interface SessionAnalytics {
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total_sessions: number;
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avg_duration_minutes: number;
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avg_tasks_per_session: number;
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avg_commits_per_session: number;
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avg_notes_per_session: number;
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total_tokens_used: number;
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}
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/**
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* Get productivity analytics for sessions
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*/
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export async function sessionProductivityAnalytics(args: SessionAnalyticsArgs): Promise<SessionAnalytics> {
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const { project, time_period = 'month' } = args;
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// Map time period to interval
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const intervalMap = {
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week: '7 days',
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month: '30 days',
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quarter: '90 days',
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};
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const interval = intervalMap[time_period];
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const sql = `
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WITH session_stats AS (
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SELECT
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s.id,
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s.duration_minutes,
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s.token_count,
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COUNT(DISTINCT ta.task_id) as tasks_touched,
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COUNT(DISTINCT sc.commit_sha) as commits_made,
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COUNT(sn.id) as notes_created
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FROM sessions s
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LEFT JOIN task_activity ta ON s.id = ta.session_id
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LEFT JOIN session_commits sc ON s.id = sc.session_id
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LEFT JOIN session_notes sn ON s.id = sn.session_id
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WHERE s.status = 'completed'
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AND s.started_at >= NOW() - INTERVAL '${interval}'
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${project ? 'AND s.project = $1' : ''}
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GROUP BY s.id, s.duration_minutes, s.token_count
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)
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SELECT
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COUNT(*)::int as total_sessions,
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COALESCE(AVG(duration_minutes), 0)::int as avg_duration_minutes,
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COALESCE(AVG(tasks_touched), 0)::numeric(10,1) as avg_tasks_per_session,
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COALESCE(AVG(commits_made), 0)::numeric(10,1) as avg_commits_per_session,
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COALESCE(AVG(notes_created), 0)::numeric(10,1) as avg_notes_per_session,
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COALESCE(SUM(token_count), 0)::bigint as total_tokens_used
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FROM session_stats;
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`;
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const result = await queryOne<SessionAnalytics>(sql, project ? [project] : []);
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return result || {
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total_sessions: 0,
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avg_duration_minutes: 0,
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avg_tasks_per_session: 0,
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avg_commits_per_session: 0,
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avg_notes_per_session: 0,
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total_tokens_used: 0,
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};
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}
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interface SessionPatternArgs {
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project?: string;
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pattern_type?: 'tool_usage' | 'task_types' | 'error_frequency';
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}
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interface Pattern {
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pattern: string;
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frequency: number;
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avg_session_duration: number;
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sessions_count: number;
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}
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/**
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* Detect patterns across sessions (tool usage, task types, etc.)
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*/
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export async function sessionPatternDetection(args: SessionPatternArgs): Promise<Pattern[]> {
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const { project, pattern_type = 'tool_usage' } = args;
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if (pattern_type === 'tool_usage') {
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// Analyze tool usage patterns
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const sql = `
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SELECT
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unnest(s.tools_used) as pattern,
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COUNT(*) as frequency,
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AVG(s.duration_minutes)::int as avg_session_duration,
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COUNT(DISTINCT s.id) as sessions_count
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FROM sessions s
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WHERE s.status = 'completed'
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AND s.tools_used IS NOT NULL
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${project ? 'AND s.project = $1' : ''}
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GROUP BY pattern
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HAVING COUNT(*) > 3
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ORDER BY frequency DESC
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LIMIT 20;
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`;
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const results = await query<Pattern>(sql, project ? [project] : []);
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return results;
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} else if (pattern_type === 'task_types') {
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// Analyze task type patterns
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const sql = `
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SELECT
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t.type as pattern,
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COUNT(*) as frequency,
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AVG(s.duration_minutes)::int as avg_session_duration,
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COUNT(DISTINCT s.id) as sessions_count
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FROM sessions s
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JOIN task_activity ta ON s.id = ta.session_id
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JOIN tasks t ON ta.task_id = t.id
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WHERE s.status = 'completed'
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${project ? 'AND s.project = $1' : ''}
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GROUP BY t.type
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HAVING COUNT(*) > 3
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ORDER BY frequency DESC;
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`;
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const results = await query<Pattern>(sql, project ? [project] : []);
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return results;
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}
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return [];
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}
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