progressive-estimation

# Progressive Estimation Estimate AI-assisted and hybrid human+agent development work using research-backed formulas with PERT statistics, confidence bands, and calibration feedback loops. ## Overview Progressive Estimation adapts to your team's working mode — human-only, hybrid, or agent-first — applying the right velocity model and multipliers for each. It produces statistical estimates rather than gut feelings. ## When to Use This Skill - Estimating development tasks where AI agents handle part of the work - Sprint planning with hybrid human+agent teams - Batch sizing a backlog (handles 5 or 500 issues) - Staffing and capacity planning with agent multipliers - Release date forecasting with confidence intervals ## How It Works 1. **Mode Detection** — Determines if the team works human-only, hybrid, or agent-first 2. **Task Classification** — Categorizes by size (XS–XL), complexity, and risk 3. **Formula Application** — Applies research-backed multipliers grounded in empirical studies 4. **PERT Calculation** — Produces expected values using three-point estimation 5. **Confidence Bands** — Generates P50, P75, P90 intervals 6. **Output Formatting** — Formats for Linear, JIRA, ClickUp, GitHub Issues, Monday, or GitLab 7. **Calibration** — Feeds back actuals to improve future estimates ## Examples **Single task:** > "Estimate building a REST API with authentication using Claude Code" **Batch mode:** > "Estimate these 12 JIRA tickets for our next sprint" **With context...