data-analysis

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AI-powered data analysis for Empathy Ledger. Use when working with themes, quotes, story suggestions, transcript analysis, storyteller connections, or any feature requiring extracted insights. Ensures consistent analysis patterns across the platform.

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When & Why to Use This Skill

This Claude skill provides a specialized AI-powered framework for qualitative data analysis and automated insight extraction. Designed for the Empathy Ledger platform, it streamlines the process of transforming raw transcripts and stories into structured metadata, including themes, key quotes, and summaries. By standardizing analysis patterns, it enhances data discoverability and ensures consistent content enrichment across storytelling databases.

Use Cases

  • Automated Transcript Analysis: Extracting cultural themes, key quotes, and AI-generated summaries from raw interview transcripts to populate database records.
  • Content Recommendation Systems: Leveraging extracted themes and storyteller connections to suggest related stories and build intelligent content links.
  • Thematic Search and Filtering: Implementing advanced search capabilities based on AI-identified categories such as 'resilience', 'knowledge', and 'land'.
  • Analytics Dashboard Integration: Using structured analysis results to generate reports on theme frequency, cultural tag distribution, and connection strength between storytellers.
namedata-analysis
descriptionAI-powered data analysis for Empathy Ledger - themes, quotes, story suggestions, transcript analysis.

Data Analysis

Patterns for AI-powered analysis: themes, quotes, summaries, and story suggestions.

When to Use

  • Adding quotes to story cards
  • Implementing story suggestions/related content
  • Building theme-based filtering or search
  • Creating analytics dashboards
  • Integrating AI analysis results

Quick Reference

Analysis Pipeline

Transcript → AI Analysis → themes[], key_quotes[], ai_summary
Story → Connections → Related Stories, Suggested Content

Key Tables

Table Analysis Fields
transcripts themes, key_quotes, ai_summary, ai_processing_status
stories themes, cultural_tags, featured_quote
storytellers expertise_themes, connection_strength

Theme Categories

  • cultural: identity, heritage, tradition, language, ceremony
  • family: kinship, elders, children, ancestors, community
  • land: country, connection, seasons, wildlife, sacred-sites
  • resilience: survival, adaptation, strength, healing, hope
  • knowledge: wisdom, teaching, learning, stories, dreams

Common Queries

-- Stories with matching theme
SELECT * FROM stories WHERE themes && ARRAY['identity', 'heritage'];

-- Theme frequency
SELECT unnest(themes) as theme, count(*) FROM stories GROUP BY theme ORDER BY count DESC;

API Endpoints

Endpoint Purpose
POST /api/transcripts/{id}/analyze Trigger AI analysis
GET /api/stories/{id}/suggestions Get related stories
GET /api/themes List themes with counts

Reference Files

Topic File
Code patterns refs/analysis-patterns.md
SQL queries refs/supabase-queries.md
Theme hierarchy refs/theme-taxonomy.md
Sync status refs/sync-status.md

Related Skills

  • database-navigator - Database exploration
  • supabase-connection - Database clients
  • design-component - UI patterns for analysis display