tools-only 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:
- customer-success-manager/ - Customer health scoring, churn risk analysis, expansion opportunities (3 Python tools)
- sales-engineer/ - Technical discovery, RFP analysis, competitive positioning, POC planning (3 Python tools)
- 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
--formatflag - Provide clear error messages for invalid input
- Return appropriate exit codes
- Process files locally (no API calls)
- Include argparse CLI with
--helpsupport
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