Agent skill · data analytics · onewave-ai
pipeline-health-analyzer
Analyze pipeline health, identify stalled deals, predict close probability, and suggest actions to move deals forward. Improves forecast accuracy and prevents revenue leakage. Use when deals get stuck or forecast accuracy is poor.
Why this skill is useful
Provides specific methodologies and templates for analyzing pipeline health and forecasting that the AI wouldn't reliably generate on its own.
What it needs
About 2k tokens when loaded. Last updated 2026-07-15. 242 stars on the source repository.
What this skill does
Pipeline Health Analyzer Identify pipeline risks, predict deal outcomes, and prescribe specific actions to accelerate stalled opportunities. Contents references/output-template.md - Full report skeleton to populate. references/stage-analysis.md - Per-stage deep-dive patterns (Discovery, Demo, Proposal) and why deals stall. references/forecasting.md - Forecast tables, probability calibration, AI re-scoring, scenario planning. references/email-templates.md - Re-engagement email templates for stalled and dark deals. references/examples.md - Trigger phrases, a worked example request, and best practices. Workflow 1. Obtain the pipeline data. Request a CSV export with deal name, stage, value, rep, deal age, days in current stage, last activity date, close date, and probability if not provided. 2. Compute pipeline-by-stage metrics: deal count, total value, average deal size, average days in stage, and stage-to-stage conversion rates. Compare each against historical benchmarks. 3. Score each deal across six health dimensions: stage velocity, engagement level, qualification depth, stakeholder coverage, competitive position, and 30-day momentum. 4. Identify stalled and at-risk deals. Flag deals exceeding benchmark time in stage, with no recent activity, with slipped close dates, or with single-threaded contacts. 5. For each critical deal, determine the root cause and prescribe prioritized actions (immediate, this-week, backstop). Pull re-engagement copy from references/email-templates.md. 6. Build the forecast: categorize deals (Commit/Best Case/Pipeline/Upside), calculate weighted and risk-adjusted value, check probability calibration against actual close rates, and re-score outliers. Follow references/forecasting.md. 7. Model best-case, expected, and worst-case scenarios against quota, with a mitigation plan for the downside. 8. Produce strategic recommendations across immediate, short-term, and long-term horizons. 9. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills onewave-ai/pipeline-health-analyzer