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.claude-plugin/plugin.json

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+{
+  "name": "catalyst-analytics",
+  "description": "Product analytics with PostHog MCP integration. Enable when analyzing user behavior, conversion metrics, and product usage. ~40k context tokens when enabled.",
+  "version": "1.0.1",
+  "author": {
+    "name": "Coalesce Labs",
+    "email": "hello@coalesce.dev",
+    "url": "https://github.com/coalesce-labs"
+  },
+  "commands": [
+    "./commands"
+  ]
+}

README.md

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+# catalyst-analytics
+
+Product analytics with PostHog MCP integration. Enable when analyzing user behavior, conversion metrics, and product usage. ~40k context tokens when enabled.

commands/analyze_user_behavior.md

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+---
+description: Analyze user behavior patterns and cohorts using PostHog
+category: analytics
+tools: Task, TodoWrite
+model: inherit
+version: 1.0.0
+---
+
+# Analyze User Behavior
+
+Query PostHog to understand user behavior patterns, cohorts, and product usage.
+
+## Prerequisites
+
+- PostHog MCP must be enabled (this plugin should be enabled)
+- `POSTHOG_AUTH_HEADER` environment variable configured
+- Access to PostHog project
+
+## Usage
+
+```bash
+/analyze-user-behavior <query>
+
+Examples:
+  /analyze-user-behavior "checkout abandonment last 30 days"
+  /analyze-user-behavior "feature adoption for new dashboard"
+  /analyze-user-behavior "user retention cohorts by signup month"
+```
+
+## What This Command Does
+
+Uses PostHog MCP tools to:
+
+1. Query user events and properties
+2. Analyze cohorts and segments
+3. Calculate conversion metrics
+4. Identify behavior patterns
+5. Generate insights with charts/data
+
+## Available PostHog Capabilities
+
+When this plugin is enabled, you have access to ~43 PostHog tools:
+
+**User Analysis**:
+
+- Query user properties and events
+- Segment users by behavior
+- Track user journeys
+- Analyze cohort retention
+
+**Product Metrics**:
+
+- Feature usage tracking
+- Conversion funnel analysis
+- A/B test results
+- Session replay analysis
+
+**Trends & Insights**:
+
+- Event trends over time
+- User engagement metrics
+- Feature adoption rates
+- Custom dashboard queries
+
+## Example Queries
+
+### Conversion Analysis
+
+```bash
+/analyze-user-behavior "Show conversion rate from signup to first purchase, broken down by traffic source"
+```
+
+### Feature Adoption
+
+```bash
+/analyze-user-behavior "How many users adopted the new search feature in the last week?"
+```
+
+### Retention Cohorts
+
+```bash
+/analyze-user-behavior "Show weekly retention for users who signed up in December 2024"
+```
+
+### User Journey
+
+```bash
+/analyze-user-behavior "What's the typical path users take before upgrading to paid plan?"
+```
+
+## Output Format
+
+The command will:
+
+1. Translate your natural language query to PostHog API calls
+2. Fetch relevant data
+3. Present findings with:
+   - Key metrics and numbers
+   - Trends and patterns
+   - Visualizations (when possible)
+   - Actionable insights
+
+## Tips
+
+- Be specific about time ranges ("last 30 days", "this quarter")
+- Mention specific events or features by name
+- Ask for comparisons ("vs last month", "broken down by...")
+- Request segmentation ("by country", "by plan type")
+
+## Context Cost
+
+**This plugin adds ~40,645 tokens** to your context window. Disable when not analyzing metrics:
+
+```bash
+/plugin disable catalyst-analytics
+```
+
+---
+
+**See also**: `/product-metrics`, `/segment-analysis`

commands/product_metrics.md

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+---
+description: View key product metrics, KPIs, and conversion rates from PostHog
+category: analytics
+tools: Task, TodoWrite
+model: inherit
+version: 1.0.0
+---
+
+# Product Metrics Dashboard
+
+Query PostHog for key product metrics, KPIs, and performance indicators.
+
+## Usage
+
+```bash
+/product-metrics [metric-type] [time-range]
+
+Examples:
+  /product-metrics "overall KPIs last 30 days"
+  /product-metrics "conversion rates this quarter"
+  /product-metrics "feature usage breakdown this week"
+```
+
+## Available Metrics
+
+### Conversion Metrics
+
+- Signup conversion rate
+- Trial to paid conversion
+- Checkout completion rate
+- Feature activation rate
+
+### Engagement Metrics
+
+- Daily/Weekly/Monthly Active Users (DAU/WAU/MAU)
+- Session duration
+- Feature usage frequency
+- User retention rates
+
+### Business Metrics
+
+- Revenue per user
+- Customer acquisition cost
+- Lifetime value
+- Churn rate
+
+### Feature Metrics
+
+- Feature adoption rate
+- Time to first use
+- Feature retention
+- Power user identification
+
+## Example Queries
+
+### Overall Dashboard
+
+```bash
+/product-metrics "Show me our key metrics for last month: MAU, conversion rates, and top features"
+```
+
+### Conversion Funnel
+
+```bash
+/product-metrics "Breakdown of our signup to paid funnel with drop-off rates at each step"
+```
+
+### Feature Performance
+
+```bash
+/product-metrics "Compare usage of our top 5 features over the last quarter"
+```
+
+### Cohort Performance
+
+```bash
+/product-metrics "How do our December signups compare to November in terms of activation and retention?"
+```
+
+## Output Format
+
+Results typically include:
+
+- **Metric values** with trend indicators (↑↓)
+- **Comparisons** to previous periods
+- **Breakdowns** by segment when relevant
+- **Top performers** and bottom performers
+- **Recommendations** based on data
+
+## Time Range Options
+
+- `today`, `yesterday`
+- `last 7 days`, `last 30 days`, `last 90 days`
+- `this week`, `last week`
+- `this month`, `last month`, `this quarter`
+- Custom: `2024-01-01 to 2024-03-31`
+
+## Segmentation
+
+Add segmentation to any query:
+
+```bash
+/product-metrics "MAU by country"
+/product-metrics "conversion rates by traffic source"
+/product-metrics "feature usage by plan type"
+```
+
+## Context Management
+
+This plugin consumes ~40k tokens. Disable after viewing metrics:
+
+```bash
+/plugin disable catalyst-analytics
+```
+
+---
+
+**See also**: `/analyze-user-behavior`, `/segment-analysis`

commands/segment_analysis.md

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+---
+description: Analyze user segments and cohorts for targeted insights
+category: analytics
+tools: Task, TodoWrite
+model: inherit
+version: 1.0.0
+---
+
+# Segment Analysis
+
+Deep-dive into specific user segments, cohorts, or customer groups using PostHog data.
+
+## Usage
+
+```bash
+/segment-analysis <segment-description>
+
+Examples:
+  /segment-analysis "users from paid plans vs free plans"
+  /segment-analysis "power users who use feature X daily"
+  /segment-analysis "users who churned in last 30 days"
+  /segment-analysis "cohort: signed up in Q4 2024"
+```
+
+## What This Analyzes
+
+### User Segments
+
+- By plan type (free, pro, enterprise)
+- By geography (country, region)
+- By acquisition source (organic, paid, referral)
+- By behavior (power users, casual users, at-risk)
+
+### Cohort Analysis
+
+- By signup date (monthly, weekly cohorts)
+- By first feature used
+- By activation milestone reached
+- By engagement level
+
+### Comparison Analysis
+
+- Segment A vs Segment B
+- Before/after feature launch
+- Treatment vs control (A/B tests)
+- Time period comparisons
+
+## Example Analyses
+
+### Plan Comparison
+
+```bash
+/segment-analysis "Compare engagement patterns between free and paid users: session frequency, feature usage, retention"
+```
+
+### Power User Identification
+
+```bash
+/segment-analysis "Identify our power users: who are they, what features do they use, what's their profile?"
+```
+
+### Churn Analysis
+
+```bash
+/segment-analysis "Analyze users who churned: what were their last actions, which features didn't they use?"
+```
+
+### Geographic Performance
+
+```bash
+/segment-analysis "Compare conversion rates and engagement across our top 5 countries"
+```
+
+### Cohort Retention
+
+```bash
+/segment-analysis "Show retention curves for each monthly signup cohort in 2024"
+```
+
+## Output Format
+
+Analysis typically includes:
+
+- **Segment characteristics** (size, demographics, behavior)
+- **Key metrics** for each segment
+- **Comparative insights** between segments
+- **Behavior patterns** unique to segment
+- **Recommendations** for targeting or improvement
+
+## Segmentation Criteria
+
+You can segment by:
+
+- **Demographics**: Country, language, device type
+- **Behavior**: Feature usage, session frequency, engagement score
+- **Business**: Plan type, payment history, LTV
+- **Temporal**: Signup date, last active, tenure
+- **Custom**: Any event or property in PostHog
+
+## Advanced Analysis
+
+### Multi-dimensional Segmentation
+
+```bash
+/segment-analysis "Power users (5+ sessions/week) from enterprise plans who use feature X"
+```
+
+### Funnel by Segment
+
+```bash
+/segment-analysis "Compare signup to activation funnel for organic vs paid traffic"
+```
+
+### Retention by Segment
+
+```bash
+/segment-analysis "30-day retention by initial feature used"
+```
+
+## Tips for Better Analysis
+
+1. **Be specific** - Define your segment clearly
+2. **Ask for comparisons** - "vs" between segments reveals insights
+3. **Look for patterns** - What makes segments different?
+4. **Consider time** - Trends over time matter
+5. **Combine criteria** - Multi-dimensional segments can be revealing
+
+## Context Cost
+
+Plugin uses ~40k tokens. Disable when analysis is complete:
+
+```bash
+/plugin disable catalyst-analytics
+```
+
+---
+
+**See also**: `/analyze-user-behavior`, `/product-metrics`

plugin.lock.json

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