Revenue Operations
Analyzes pipeline coverage, tracks forecast accuracy with MAPE, and calculates GTM...
Install
npx skills add borghei/Claude-Skills --skill revenue-operations -g -a claude-code -y- Repository
- borghei/Claude-Skills1k
- Category
- Engineering
- Updated
- 12d ago
- License
- MIT + Commons Clause
- Context cost
- Mediumabout 3,000 tokens
- Runs scripts
- Yes, review before use
What it does
Analyzes pipeline coverage, tracks forecast accuracy with MAPE, and calculates GTM efficiency metrics for SaaS revenue optimization
Revenue Operations
Pipeline analysis, forecast accuracy tracking, and GTM efficiency measurement for SaaS revenue teams.
Table of Contents
Clarify First
Before running the analysis, settle the inputs below. When one is missing or vague and would change the result, ask about it; when it wouldn't, use a sensible default and say which one you used.
- Which analysis: pipeline health, forecast accuracy, or GTM efficiency (selects the script and its input schema).
- Quota / target: the number pipeline coverage and Magic Number are measured against.
- Data export readiness: deals with stage/value/age/close-date, or forecast-vs-actual periods (the tools consume specific JSON; forecast trend needs 3+ periods).
- Company stage + sales motion: seed vs growth, PLG vs enterprise (benchmarks vary widely by stage and motion).
Ask about the two or three inputs that matter most for this request, not the whole list. If the user wants a result straight away, produce it and state your assumptions at the top.
Quick Start
# Analyze pipeline health and coverage
python scripts/pipeline_analyzer.py --input assets/sample_pipeline_data.json --format text
# Track forecast accuracy over multiple periods
python scripts/forecast_accuracy_tracker.py assets/sample_forecast_data.json --format text
