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From antigravity-awesome-skills
Estimates AI-assisted and hybrid human+agent development tasks using PERT statistics, confidence bands, and calibration feedback for sprint planning and capacity forecasting.
How this skill is triggered — by the user, by Claude, or both
Slash command
/antigravity-awesome-skills:progressive-estimationThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Estimate AI-assisted and hybrid human+agent development work using research-backed formulas with PERT statistics, confidence bands, and calibration feedback loops.
Estimate AI-assisted and hybrid human+agent development work using research-backed formulas with PERT statistics, confidence bands, and calibration feedback loops.
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.
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:
"We have 3 developers using AI agents for ~60% of implementation. Estimate this feature."
Problem: Overconfident estimates Solution: Use P75 or P90 for commitments, not P50
Problem: Missing context Solution: The skill asks clarifying questions — provide team size and agent usage
Problem: Stale calibration Solution: Re-calibrate when team composition or tooling changes significantly
@sprint-planning - Sprint planning and backlog management@project-management - General project management workflows@capacity-planning - Team velocity and capacity planningnpx claudepluginhub sickn33/antigravity-awesome-skills --plugin antigravity-awesome-skillsEstimate AI-assisted and hybrid human+agent development work with research-backed PERT statistics and calibration feedback loops
Estimates effort, cost, duration, and complexity for projects, features, and tasks using analogous, parametric, three-point, and expert judgment methods. For planning and forecasting.
Replaces single-point guesses with structured three-point PERT estimates (best/likely/worst) including confidence intervals, unknowns, and assumptions. Useful for effort estimation, story pointing, or t-shirt sizing.