90 lines
3.4 KiB
Markdown
90 lines
3.4 KiB
Markdown
---
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name: progressive-estimation
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description: "Estimate AI-assisted and hybrid human+agent development work with research-backed PERT statistics and calibration feedback loops"
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category: project-management
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risk: safe
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source: community
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date_added: "2026-03-10"
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author: Enreign
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tags:
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- estimation
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- project-management
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- pert
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- sprint-planning
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- ai-agents
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tools:
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- claude
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---
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# Progressive Estimation
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Estimate AI-assisted and hybrid human+agent development work using research-backed formulas with PERT statistics, confidence bands, and calibration feedback loops.
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## Overview
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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.
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## When to Use This Skill
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- Estimating development tasks where AI agents handle part of the work
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- Sprint planning with hybrid human+agent teams
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- Batch sizing a backlog (handles 5 or 500 issues)
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- Staffing and capacity planning with agent multipliers
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- Release date forecasting with confidence intervals
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## How It Works
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1. **Mode Detection** — Determines if the team works human-only, hybrid, or agent-first
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2. **Task Classification** — Categorizes by size (XS–XL), complexity, and risk
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3. **Formula Application** — Applies research-backed multipliers grounded in empirical studies
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4. **PERT Calculation** — Produces expected values using three-point estimation
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5. **Confidence Bands** — Generates P50, P75, P90 intervals
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6. **Output Formatting** — Formats for Linear, JIRA, ClickUp, GitHub Issues, Monday, or GitLab
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7. **Calibration** — Feeds back actuals to improve future estimates
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## Examples
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**Single task:**
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> "Estimate building a REST API with authentication using Claude Code"
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**Batch mode:**
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> "Estimate these 12 JIRA tickets for our next sprint"
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**With context:**
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> "We have 3 developers using AI agents for ~60% of implementation. Estimate this feature."
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## Best Practices
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- Start with a single task to calibrate before moving to batch mode
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- Feed back actual completion times to improve the calibration system
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- Use "instant mode" for quick T-shirt sizing without full PERT analysis
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- Be explicit about team composition and agent usage percentage
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## Common Pitfalls
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- **Problem:** Overconfident estimates
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**Solution:** Use P75 or P90 for commitments, not P50
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- **Problem:** Missing context
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**Solution:** The skill asks clarifying questions — provide team size and agent usage
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- **Problem:** Stale calibration
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**Solution:** Re-calibrate when team composition or tooling changes significantly
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## Related Skills
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- `@sprint-planning` - Sprint planning and backlog management
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- `@project-management` - General project management workflows
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- `@capacity-planning` - Team velocity and capacity planning
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## Additional Resources
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- [Source Repository](https://github.com/Enreign/progressive-estimation)
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- [Installation Guide](https://github.com/Enreign/progressive-estimation/blob/main/INSTALLATION.md)
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- [Research References](https://github.com/Enreign/progressive-estimation/tree/main/references)
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## Limitations
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- Use this skill only when the task clearly matches the scope described above.
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- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
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- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
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