Business & Growth Skills - Claude Code Guidance

This guide covers the 3 production-ready business and growth skills and their Python automation tools.

Business & Growth Skills Overview

Available Skills:

1. customer-success-manager/ - Customer health scoring, churn risk analysis, expansion opportunities (3 Python tools)
2. sales-engineer/ - Technical discovery, RFP analysis, competitive positioning, POC planning (3 Python tools)
3. revenue-operations/ - Pipeline analysis, forecast accuracy, GTM efficiency metrics (3 Python tools)

Total Tools: 9 Python automation tools, 9 knowledge bases, 19+ templates

Python Automation Tools

Customer Success Manager Tools

1. Health Score Calculator (customer-success-manager/scripts/health_score_calculator.py)

Purpose: Multi-dimensional customer health scoring with trend analysis

Features:

• Weighted scoring across 4 dimensions (usage, engagement, support, relationship)
• Red/Yellow/Green classification with configurable thresholds
• Trend analysis comparing current vs previous period
• Segment-aware benchmarking (Enterprise/Mid-Market/SMB)

Usage:

python customer-success-manager/scripts/health_score_calculator.py customer_data.json
python customer-success-manager/scripts/health_score_calculator.py customer_data.json --format json

2. Churn Risk Analyzer (customer-success-manager/scripts/churn_risk_analyzer.py)

Purpose: Identify at-risk accounts with intervention recommendations

Features:

• Risk scoring based on behavioral signals
• Warning signal detection and categorization
• Tier-appropriate intervention playbooks
• Urgency-based prioritization

Usage:

python customer-success-manager/scripts/churn_risk_analyzer.py customer_data.json
python customer-success-manager/scripts/churn_risk_analyzer.py customer_data.json --format json

3. Expansion Opportunity Scorer (customer-success-manager/scripts/expansion_opportunity_scorer.py)

Purpose: Identify upsell and cross-sell opportunities

Features:

• Adoption depth analysis across product modules
• Whitespace mapping for unused features
• Revenue opportunity estimation
• Priority ranking by effort and impact

Usage:

python customer-success-manager/scripts/expansion_opportunity_scorer.py customer_data.json
python customer-success-manager/scripts/expansion_opportunity_scorer.py customer_data.json --format json

Sales Engineer Tools

4. RFP Response Analyzer (sales-engineer/scripts/rfp_response_analyzer.py)

Purpose: Score RFP/RFI coverage and identify gaps

Features:

• Requirement coverage scoring (Full/Partial/Planned/Gap)
• Effort estimation per requirement
• Gap identification with mitigation strategies
• Overall bid/no-bid recommendation

Usage:

python sales-engineer/scripts/rfp_response_analyzer.py rfp_data.json
python sales-engineer/scripts/rfp_response_analyzer.py rfp_data.json --format json

5. Competitive Matrix Builder (sales-engineer/scripts/competitive_matrix_builder.py)

Purpose: Generate feature comparison matrices and competitive positioning

Features:

• Feature-by-feature comparison matrix
• Competitive scoring with weighted categories
• Differentiator identification
• Battlecard-ready output

Usage:

python sales-engineer/scripts/competitive_matrix_builder.py competitive_data.json
python sales-engineer/scripts/competitive_matrix_builder.py competitive_data.json --format json

6. POC Planner (sales-engineer/scripts/poc_planner.py)

Purpose: Plan proof-of-concept engagements

Features:

• Timeline estimation based on scope
• Resource allocation planning
• Success criteria definition
• Evaluation scorecard generation

Usage:

python sales-engineer/scripts/poc_planner.py poc_data.json
python sales-engineer/scripts/poc_planner.py poc_data.json --format json

Revenue Operations Tools

7. Pipeline Analyzer (revenue-operations/scripts/pipeline_analyzer.py)

Purpose: Analyze sales pipeline health and velocity

Features:

• Coverage ratio calculation (pipeline/quota)
• Stage conversion rate analysis
• Sales velocity metrics (4-lever model)
• Deal aging analysis

Usage:

python revenue-operations/scripts/pipeline_analyzer.py pipeline_data.json
python revenue-operations/scripts/pipeline_analyzer.py pipeline_data.json --format json

8. Forecast Accuracy Tracker (revenue-operations/scripts/forecast_accuracy_tracker.py)

Purpose: Measure and improve forecast accuracy

Features:

• MAPE (Mean Absolute Percentage Error) calculation
• Forecast bias detection (over/under-forecasting)
• Period-over-period trend analysis
• Category-level accuracy breakdown

Usage:

python revenue-operations/scripts/forecast_accuracy_tracker.py forecast_data.json
python revenue-operations/scripts/forecast_accuracy_tracker.py forecast_data.json --format json

9. GTM Efficiency Calculator (revenue-operations/scripts/gtm_efficiency_calculator.py)

Purpose: Calculate go-to-market efficiency metrics

Features:

• Magic number calculation
• LTV:CAC ratio analysis
• CAC payback period
• Burn multiple assessment
• Industry benchmarking

Usage:

python revenue-operations/scripts/gtm_efficiency_calculator.py gtm_data.json
python revenue-operations/scripts/gtm_efficiency_calculator.py gtm_data.json --format json

Quality Standards

All business & growth Python tools must:

• Use standard library only (no external dependencies)
• Support both JSON and human-readable output via --format flag
• Provide clear error messages for invalid input
• Return appropriate exit codes
• Process files locally (no API calls)
• Include argparse CLI with --help support

Related Skills

• Marketing: Content creation, demand generation -> ../marketing-skill/
• Product Team: User research, feature prioritization -> ../product-team/
• C-Level: Strategic planning -> ../c-level-advisor/
• Engineering: Technical implementation -> ../engineering-team/

Last Updated: February 2026 Skills Deployed: 3/3 business & growth skills production-ready Total Tools: 9 Python automation tools