Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
Version History
v2.1.1 release
What This Skill Does
Three Python scripts for analyzing sales pipeline health, tracking forecast accuracy, and calculating GTM efficiency metrics. Takes JSON input files with deal, forecast, or cost data and outputs metrics with ratings and industry benchmarks. Supports text and JSON output formats for both human review and dashboard integration.
Combines pipeline health, forecast accuracy, and GTM efficiency analysis in a single offline toolkit without requiring CRM vendor-specific reporting modules or a separate BI tool.
When to use it
- Weekly pipeline coverage check before a sales team meeting
- Identifying reps with systematic over- or under-forecasting patterns
- Board prep with Magic Number, LTV:CAC, and Rule of 40 calculations
- Flagging deals that have stalled past their expected stage cycle time
- Quarterly GTM efficiency audit comparing S&M spend against net new ARR
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: analyze pipeline coverage from current_pipeline.json
- 1Loads the pipeline JSON with deal stages, values, close dates, and quota target
- 2Calculates pipeline coverage ratio and flags quarters below 3x quota
- 3Computes stage-to-stage conversion rates and sales velocity
- 4Flags deals exceeding 2x average cycle time per stage as aging risks
- 5Identifies concentration risk when any single deal exceeds 40% of total pipeline value
Text report with coverage ratio, aging deal list, conversion rates, velocity metrics, and recommended action items