Agent skill · data analytics · alirezarezvani
revenue-operations
Check sales pipeline and forecasts: pipeline coverage, forecast accuracy, magic number, CAC payback. Use whenever the user asks if pipeline is enough or how good forecasts are.
Why this skill is useful
Adds 3 executable scripts for analyzing sales pipeline health, tracking forecast accuracy, and calculating GTM efficiency that aren't in public docs.
What it needs
Requires python installed locally. About 5k tokens when loaded. Last updated 2026-08-05. 23,939 stars on the source repository.
What this skill does
Revenue Operations Pipeline analysis, forecast accuracy tracking, and GTM efficiency measurement for SaaS revenue teams. Output formats: All scripts support --format text (human-readable) and --format json (dashboards/integrations). --- Quick Start --- Tools Overview 1. Pipeline Analyzer Analyzes sales pipeline health including coverage ratios, stage conversion rates, deal velocity, aging risks, and concentration risks. Input: JSON file with deals, quota, and stage configuration Output: Coverage ratios, conversion rates, velocity metrics, aging flags, risk assessment Usage: Key Metrics Calculated: Pipeline Coverage Ratio -- Total pipeline value / quota target (healthy: 3-4x) Stage Conversion Rates -- Stage-to-stage progression rates Sales Velocity -- (Opportunities x Avg Deal Size x Win Rate) / Avg Sales Cycle Deal Aging -- Flags deals exceeding 2x average cycle time per stage Concentration Risk -- Warns when >40% of pipeline is in a single deal Coverage Gap Analysis -- Identifies quarters with insufficient pipeline Input Schema: 2. Forecast Accuracy Tracker Tracks forecast accuracy over time using MAPE, detects systematic bias, analyzes trends, and provides category-level breakdowns. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills alirezarezvani/revenue-operations--bcf4b1