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feat: add Conductor plugin for Context-Driven Development

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Add comprehensive Conductor plugin implementing Context-Driven Development
methodology with tracks, specs, and phased implementation plans.

Components:
- 5 commands: setup, new-track, implement, status, revert
- 1 agent: conductor-validator
- 3 skills: context-driven-development, track-management, workflow-patterns
- 18 templates for project artifacts

Documentation updates:
- README.md: Updated counts (68 plugins, 100 agents, 110 skills, 76 tools)
- docs/plugins.md: Added Conductor to Workflows section
- docs/agents.md: Added conductor-validator agent
- docs/agent-skills.md: Added Conductor skills section

Also includes Prettier formatting across all project files.
This commit is contained in:
Seth Hobson
2026-01-15 17:38:21 -05:00
parent 87231b828d
commit f662524f9a
94 changed files with 11610 additions and 1728 deletions
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15
plugins/business-analytics/agents/business-analyst.md
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@@ -7,11 +7,13 @@ model: sonnet
You are an expert business analyst specializing in data-driven decision making through advanced analytics, modern BI tools, and strategic business intelligence.
## Purpose
Expert business analyst focused on transforming complex business data into actionable insights and strategic recommendations. Masters modern analytics platforms, predictive modeling, and data storytelling to drive business growth and optimize operational efficiency. Combines technical proficiency with business acumen to deliver comprehensive analysis that influences executive decision-making.
## Capabilities
### Modern Analytics Platforms and Tools
- Advanced dashboard creation with Tableau, Power BI, Looker, and Qlik Sense
- Cloud-native analytics with Snowflake, BigQuery, and Databricks
- Real-time analytics and streaming data visualization
@@ -21,6 +23,7 @@ Expert business analyst focused on transforming complex business data into actio
- Automated report generation and distribution systems
### AI-Powered Business Intelligence
- Machine learning for predictive analytics and forecasting
- Natural language processing for sentiment and text analysis
- AI-driven anomaly detection and alerting systems
@@ -30,6 +33,7 @@ Expert business analyst focused on transforming complex business data into actio
- Recommendation engines for business optimization
### Strategic KPI Framework Development
- Comprehensive KPI strategy design and implementation
- North Star metrics identification and tracking
- OKR (Objectives and Key Results) framework development
@@ -39,6 +43,7 @@ Expert business analyst focused on transforming complex business data into actio
- KPI benchmarking against industry standards
### Financial Analysis and Modeling
- Advanced revenue modeling and forecasting techniques
- Customer lifetime value (CLV) and acquisition cost (CAC) optimization
- Cohort analysis and retention modeling
@@ -48,6 +53,7 @@ Expert business analyst focused on transforming complex business data into actio
- Investment analysis and ROI calculations
### Customer and Market Analytics
- Customer segmentation and persona development
- Churn prediction and prevention strategies
- Market sizing and total addressable market (TAM) analysis
@@ -57,6 +63,7 @@ Expert business analyst focused on transforming complex business data into actio
- Voice of customer (VoC) analysis and insights
### Data Visualization and Storytelling
- Advanced data visualization techniques and best practices
- Interactive dashboard design and user experience optimization
- Executive presentation design and narrative development
@@ -66,6 +73,7 @@ Expert business analyst focused on transforming complex business data into actio
- Accessibility standards for inclusive data visualization
### Statistical Analysis and Research
- Advanced statistical analysis and hypothesis testing
- A/B testing design, execution, and analysis
- Survey design and market research methodologies
@@ -75,6 +83,7 @@ Expert business analyst focused on transforming complex business data into actio
- Statistical modeling for business applications
### Data Management and Quality
- Data governance frameworks and implementation
- Data quality assessment and improvement strategies
- Master data management and data integration
@@ -84,6 +93,7 @@ Expert business analyst focused on transforming complex business data into actio
- Privacy and compliance considerations (GDPR, CCPA)
### Business Process Optimization
- Process mining and workflow analysis
- Operational efficiency measurement and improvement
- Supply chain analytics and optimization
@@ -93,6 +103,7 @@ Expert business analyst focused on transforming complex business data into actio
- Change management for analytics initiatives
### Industry-Specific Analytics
- E-commerce and retail analytics (conversion, merchandising)
- SaaS metrics and subscription business analysis
- Healthcare analytics and population health insights
@@ -102,6 +113,7 @@ Expert business analyst focused on transforming complex business data into actio
- Human resources analytics and workforce planning
## Behavioral Traits
- Focuses on business impact and actionable recommendations
- Translates complex technical concepts for non-technical stakeholders
- Maintains objectivity while providing strategic guidance
@@ -114,6 +126,7 @@ Expert business analyst focused on transforming complex business data into actio
- Questions data quality and methodology rigorously
## Knowledge Base
- Modern BI and analytics platform ecosystems
- Statistical analysis and machine learning techniques
- Data visualization theory and design principles
@@ -126,6 +139,7 @@ Expert business analyst focused on transforming complex business data into actio
- Business strategy frameworks and analytical approaches
## Response Approach
1. **Define business objectives** and success criteria clearly
2. **Assess data availability** and quality for analysis
3. **Design analytical framework** with appropriate methodologies
@@ -136,6 +150,7 @@ Expert business analyst focused on transforming complex business data into actio
8. **Plan for ongoing monitoring** and continuous improvement
## Example Interactions
- "Analyze our customer churn patterns and create a predictive model to identify at-risk customers"
- "Build a comprehensive revenue dashboard with drill-down capabilities and automated alerts"
- "Design an A/B testing framework for our product feature releases"

80
plugins/business-analytics/skills/data-storytelling/SKILL.md
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@@ -41,11 +41,11 @@ Resolution: Insights and recommendations
### 3. Three Pillars
| Pillar | Purpose | Components |
|--------|---------|------------|
| **Data** | Evidence | Numbers, trends, comparisons |
| **Narrative** | Meaning | Context, causation, implications |
| **Visuals** | Clarity | Charts, diagrams, highlights |
| Pillar | Purpose | Components |
| ------------- | -------- | -------------------------------- |
| **Data** | Evidence | Numbers, trends, comparisons |
| **Narrative** | Meaning | Context, causation, implications |
| **Visuals** | Clarity | Charts, diagrams, highlights |
## Story Frameworks
@@ -55,35 +55,43 @@ Resolution: Insights and recommendations
# Customer Churn Analysis
## The Hook
"We're losing $2.4M annually to preventable churn."
## The Context
- Current churn rate: 8.5% (industry average: 5%)
- Average customer lifetime value: $4,800
- 500 customers churned last quarter
## The Problem
Analysis of churned customers reveals a pattern:
- 73% churned within first 90 days
- Common factor: < 3 support interactions
- Low feature adoption in first month
## The Insight
[Show engagement curve visualization]
Customers who don't engage in the first 14 days
are 4x more likely to churn.
## The Solution
1. Implement 14-day onboarding sequence
2. Proactive outreach at day 7
3. Feature adoption tracking
## Expected Impact
- Reduce early churn by 40%
- Save $960K annually
- Payback period: 3 months
## Call to Action
Approve $50K budget for onboarding automation.
```
@@ -93,29 +101,35 @@ Approve $50K budget for onboarding automation.
# Q4 Performance Analysis
## Where We Started
Q3 ended with $1.2M MRR, 15% below target.
Team morale was low after missed goals.
## What Changed
[Timeline visualization]
- Oct: Launched self-serve pricing
- Nov: Reduced friction in signup
- Dec: Added customer success calls
## The Transformation
[Before/after comparison chart]
| Metric | Q3 | Q4 | Change |
| Metric | Q3 | Q4 | Change |
|----------------|--------|--------|--------|
| Trial → Paid | 8% | 15% | +87% |
| Time to Value | 14 days| 5 days | -64% |
| Expansion Rate | 2% | 8% | +300% |
| Trial → Paid | 8% | 15% | +87% |
| Time to Value | 14 days| 5 days | -64% |
| Expansion Rate | 2% | 8% | +300% |
## Key Insight
Self-serve + high-touch creates compound growth.
Customers who self-serve AND get a success call
have 3x higher expansion rate.
## Going Forward
Double down on hybrid model.
Target: $1.8M MRR by Q2.
```
@@ -126,12 +140,15 @@ Target: $1.8M MRR by Q2.
# Market Opportunity Analysis
## The Question
Should we expand into EMEA or APAC first?
## The Comparison
[Side-by-side market analysis]
### EMEA
- Market size: $4.2B
- Growth rate: 8%
- Competition: High
@@ -139,6 +156,7 @@ Should we expand into EMEA or APAC first?
- Language: Multiple
### APAC
- Market size: $3.8B
- Growth rate: 15%
- Competition: Moderate
@@ -146,10 +164,11 @@ Should we expand into EMEA or APAC first?
- Language: Multiple
## The Analysis
[Weighted scoring matrix visualization]
| Factor | Weight | EMEA Score | APAC Score |
|-------------|--------|------------|------------|
| ----------- | ------ | ---------- | ---------- |
| Market Size | 25% | 5 | 4 |
| Growth | 30% | 3 | 5 |
| Competition | 20% | 2 | 4 |
@@ -157,11 +176,13 @@ Should we expand into EMEA or APAC first?
| **Total** | | **2.9** | **4.1** |
## The Recommendation
APAC first. Higher growth, less competition.
Start with Singapore hub (English, business-friendly).
Enter EMEA in Year 2 with localization ready.
## Risk Mitigation
- Timezone coverage: Hire 24/7 support
- Cultural fit: Local partnerships
- Payment: Multi-currency from day 1
@@ -186,22 +207,22 @@ Slide 5: "We need new segments" [add opportunity zones]
```markdown
Before/After:
┌─────────────────┬─────────────────┐
│ BEFORE │ AFTER │
│ │ │
│ Process: 5 days│ Process: 1 day │
│ Errors: 15% │ Errors: 2% │
│ Cost: $50/unit │ Cost: $20/unit │
│ BEFORE │ AFTER │
│ │ │
│ Process: 5 days│ Process: 1 day │
│ Errors: 15% │ Errors: 2% │
│ Cost: $50/unit │ Cost: $20/unit │
└─────────────────┴─────────────────┘
This/That (emphasize difference):
┌─────────────────────────────────────┐
│ CUSTOMER A vs B │
│ ┌──────────┐ ┌──────────┐ │
│ │ ████████ │ │ ██ │ │
│ │ $45,000 │ │ $8,000 │ │
│ │ LTV │ │ LTV │ │
│ └──────────┘ └──────────┘ │
│ Onboarded No onboarding │
│ CUSTOMER A vs B │
│ ┌──────────┐ ┌──────────┐ │
│ │ ████████ │ │ ██ │ │
│ │ $45,000 │ │ $8,000 │ │
│ │ LTV │ │ LTV │ │
│ └──────────┘ └──────────┘ │
│ Onboarded No onboarding │
└─────────────────────────────────────┘
```
@@ -310,36 +331,43 @@ Next steps
# Monthly Business Review: January 2024
## THE HEADLINE
Revenue up 15% but CAC increasing faster than LTV
## KEY METRICS AT A GLANCE
┌────────┬────────┬────────┬────────┐
│ MRR │ NRR │ CAC │ LTV │
│ $125K │ 108% │ $450 │ $2,200 │
│ ▲15% │ ▲3% │ ▲22% │ ▲8% │
│ MRR │ NRR │ CAC │ LTV │
│ $125K │ 108% │ $450 │ $2,200 │
│ ▲15% │ ▲3% │ ▲22% │ ▲8% │
└────────┴────────┴────────┴────────┘
## WHAT'S WORKING
✓ Enterprise segment growing 25% MoM
✓ Referral program driving 30% of new logos
✓ Support satisfaction at all-time high (94%)
## WHAT NEEDS ATTENTION
✗ SMB acquisition cost up 40%
✗ Trial conversion down 5 points
✗ Time-to-value increased by 3 days
## ROOT CAUSE
[Mini chart showing SMB vs Enterprise CAC trend]
SMB paid ads becoming less efficient.
CPC up 35% while conversion flat.
## RECOMMENDATION
1. Shift $20K/mo from paid to content
2. Launch SMB self-serve trial
3. A/B test shorter onboarding
## NEXT MONTH'S FOCUS
- Launch content marketing pilot
- Complete self-serve MVP
- Reduce time-to-value to < 7 days
@@ -403,6 +431,7 @@ Present ranges:
## Best Practices
### Do's
- **Start with the "so what"** - Lead with insight
- **Use the rule of three** - Three points, three comparisons
- **Show, don't tell** - Let data speak
@@ -410,6 +439,7 @@ Present ranges:
- **End with action** - Clear next steps
### Don'ts
- **Don't data dump** - Curate ruthlessly
- **Don't bury the insight** - Front-load key findings
- **Don't use jargon** - Match audience vocabulary

12
plugins/business-analytics/skills/kpi-dashboard-design/SKILL.md
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@@ -20,11 +20,11 @@ Comprehensive patterns for designing effective Key Performance Indicator (KPI) d
### 1. KPI Framework
| Level | Focus | Update Frequency | Audience |
|-------|-------|------------------|----------|
| **Strategic** | Long-term goals | Monthly/Quarterly | Executives |
| **Tactical** | Department goals | Weekly/Monthly | Managers |
| **Operational** | Day-to-day | Real-time/Daily | Teams |
| Level | Focus | Update Frequency | Audience |
| --------------- | ---------------- | ----------------- | ---------- |
| **Strategic** | Long-term goals | Monthly/Quarterly | Executives |
| **Tactical** | Department goals | Weekly/Monthly | Managers |
| **Operational** | Day-to-day | Real-time/Daily | Teams |
### 2. SMART KPIs
@@ -406,6 +406,7 @@ for alert in alerts:
## Best Practices
### Do's
- **Limit to 5-7 KPIs** - Focus on what matters
- **Show context** - Comparisons, trends, targets
- **Use consistent colors** - Red=bad, green=good
@@ -413,6 +414,7 @@ for alert in alerts:
- **Update appropriately** - Match metric frequency
### Don'ts
- **Don't show vanity metrics** - Focus on actionable data
- **Don't overcrowd** - White space aids comprehension
- **Don't use 3D charts** - They distort perception