Marketplace data-analysis

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.

install
source · Clone the upstream repo
git clone https://github.com/aiskillstore/marketplace
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/aiskillstore/marketplace "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/acurioustractor/data-analysis" ~/.claude/skills/aiskillstore-marketplace-data-analysis && rm -rf "$T"
manifest: skills/acurioustractor/data-analysis/SKILL.md
source content

Data Analysis Skill

This skill provides patterns and best practices for AI-powered data analysis across the Empathy Ledger platform, ensuring quotes, themes, summaries, and suggestions appear consistently everywhere.

Core Data Model

Analysis Pipeline

Transcript (raw audio/text)
    ↓ AI Analysis
Theme Extraction → themes[] array
Quote Extraction → key_quotes[] array
Summary Generation → ai_summary text
Sentiment Analysis → sentiment_scores{}
    ↓ Story Creation
Story (authored content)
    ↓ Connections
Related Stories ← theme matching
Suggested Content ← AI recommendations

Key Tables for Analysis

TableAnalysis FieldsPurpose
transcripts
themes
,
key_quotes
,
ai_summary
,
ai_processing_status
Raw interview analysis
stories
themes
,
cultural_tags
,
featured_quote
Published story metadata
storytellers
expertise_themes
,
connection_strength
Storyteller insights
story_suggestions
reason
,
confidence_score
,
theme_overlap
AI recommendations

Theme System

Standard Theme Categories

const 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']
}

Theme Extraction Pattern

// When extracting themes from content:
interface ThemeExtraction {
  themes: string[]           // Max 5-7 primary themes
  theme_confidence: number   // 0-1 confidence score
  cultural_relevance: 'high' | 'medium' | 'low'
}

// Supabase query for theme-based matching
const { data } = await supabase
  .from('stories')
  .select('*')
  .overlaps('themes', ['identity', 'heritage'])
  .order('view_count', { ascending: false })
  .limit(5)

Quote System

Quote Extraction Standards

interface ExtractedQuote {
  text: string              // The quote itself (50-300 chars ideal)
  context?: string          // Surrounding context
  themes: string[]          // Themes this quote relates to
  significance: 'highlight' | 'supporting' | 'context'
  speaker_attribution?: string
}

// Store quotes in transcripts
UPDATE transcripts SET key_quotes = ARRAY[
  'When I walk on Country, I feel my ancestors with me.',
  'Our language carries the wisdom of thousands of years.'
]

Quote Display Patterns

// Story cards should show featured quotes
<StoryCard
  story={story}
  featuredQuote={story.key_quotes?.[0]}
  showThemes={true}
/>

// Quote highlight component
<QuoteHighlight
  quote={quote}
  attribution={storyteller.display_name}
  themes={quote.themes}
/>

AI Analysis Integration

Transcript Analysis Flow

// 1. Trigger analysis
POST /api/transcripts/{id}/analyze

// 2. AI extracts:
{
  themes: ['identity', 'land-connection', 'healing'],
  key_quotes: [
    "The river taught me patience...",
    "Our stories are our survival..."
  ],
  ai_summary: "This transcript explores themes of cultural...",
  sentiment: { positive: 0.7, reflective: 0.8 }
}

// 3. Store and index
UPDATE transcripts SET
  themes = $themes,
  key_quotes = $key_quotes,
  ai_summary = $ai_summary,
  ai_processing_status = 'completed'

Story Suggestion Algorithm

// Find related content based on theme overlap
async function getSuggestedStories(storyId: string) {
  const { data: story } = await supabase
    .from('stories')
    .select('themes, storyteller_id')
    .eq('id', storyId)
    .single()

  // Find stories with overlapping themes
  const { data: related } = await supabase
    .from('stories')
    .select('*, storytellers!inner(display_name)')
    .neq('id', storyId)
    .overlaps('themes', story.themes)
    .limit(5)

  return related.map(r => ({
    ...r,
    theme_overlap: calculateOverlap(story.themes, r.themes),
    reason: generateReason(story.themes, r.themes)
  }))
}

Supabase Best Practices

Array Operations for Themes

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

-- Find stories with ALL themes
SELECT * FROM stories WHERE themes @> ARRAY['identity', 'heritage'];

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

Full-Text Search Integration

-- Add search vector for quotes
ALTER TABLE transcripts ADD COLUMN
  quote_search tsvector GENERATED ALWAYS AS (
    to_tsvector('english', array_to_string(key_quotes, ' '))
  ) STORED;

CREATE INDEX idx_quote_search ON transcripts USING GIN(quote_search);

-- Search quotes
SELECT * FROM transcripts
WHERE quote_search @@ to_tsquery('english', 'ancestor & wisdom');

Materialized View for Analytics

-- Theme analytics across platform
CREATE MATERIALIZED VIEW theme_analytics AS
SELECT
  unnest(themes) as theme,
  count(*) as story_count,
  count(DISTINCT storyteller_id) as storyteller_count,
  avg(view_count) as avg_views
FROM stories
WHERE status = 'published'
GROUP BY theme;

-- Refresh periodically
REFRESH MATERIALIZED VIEW theme_analytics;

Component Integration Points

Where Analysis Should Appear

LocationWhat to ShowSource
Story CardsFeatured quote, top 3 themes
stories.key_quotes[0]
,
stories.themes
Story DetailAll quotes, full theme listFull arrays
Storyteller ProfileExpertise themes, quote countAggregated from stories
World Tour MapTheme clusters, quote highlights
theme_analytics
view
Search ResultsTheme badges, quote snippetsFull-text search
Related StoriesTheme overlap %, suggestion reasonCalculated on query
DashboardTheme trends, popular quotesAnalytics views

React Components for Analysis

// Theme badge with cultural coloring
<ThemeBadge theme="identity" variant="cultural" />

// Quote card with attribution
<QuoteCard
  quote={quote}
  storyteller={storyteller}
  showThemes
  linkToStory
/>

// Theme cloud visualization
<ThemeCloud
  themes={allThemes}
  onThemeClick={handleFilter}
  highlightActive={activeThemes}
/>

// Story suggestions panel
<SuggestedStories
  currentStory={story}
  maxSuggestions={5}
  showReason
/>

Analysis API Endpoints

EndpointPurpose
POST /api/transcripts/{id}/analyze
Trigger AI analysis
GET /api/transcripts/{id}/analyze
Check analysis status
GET /api/stories/{id}/suggestions
Get related stories
GET /api/themes
List all themes with counts
GET /api/themes/{theme}/stories
Stories by theme
GET /api/quotes/search
Search across quotes
GET /api/storytellers/{id}/themes
Storyteller expertise

When to Use This Skill

Invoke when:

  • Adding quotes to story cards or displays
  • Implementing story suggestions/related content
  • Building theme-based filtering or search
  • Creating analytics dashboards
  • Integrating AI analysis results
  • Designing data visualization components
  • Optimizing Supabase queries for analysis data

Reference Files