progressive-estimation
Lets your agent estimate time and effort for projects. It uses statistics and feedback for more accurate predictions.
What it does
This tool helps predict how long software development tasks will take, especially when using artificial intelligence. It uses statistics to provide more accurate estimates than a guess.
When to use it
- ✓To plan tasks that involve AI.
- ✓When organizing a group of tasks for a project.
- ✓To know when a project can be delivered.
Example of what to ask your AI
“Estimate how long it will take to build a simple website using an AI assistant.”
Want more? Open the sections below.
How to use
The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.
Skill link
Ready-to-paste message
How it works
The tool analyzes the task type, size, and risk. Then, it uses formulas based on real data to calculate the estimated time and the probability of accuracy.
Installation
Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.
In the terminal (Claude Code, Codex, Cursor), in your project folder:
npx skills add sickn33/agentic-awesome-skills --skill progressive-estimationOr download just the file:
curl -L https://raw.githubusercontent.com/sickn33/agentic-awesome-skills/main/plugins/agentic-awesome-skills-claude/skills/progressive-estimation/SKILL.md -o SKILL.mdTechnical content (original SKILL.md)
Original text by the author, straight from GitHub.
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
- Mode Detection — Determines if the team works human-only, hybrid, or agent-first
- Task Classification — Categorizes by size (XS–XL), complexity, and risk
- Formula Application — Applies research-backed multipliers grounded in empirical studies
- PERT Calculation — Produces expected values using three-point estimation
- Confidence Bands — Generates P50, P75, P90 intervals
- Output Formatting — Formats for Linear, JIRA, ClickUp, GitHub Issues, Monday, or GitLab
- 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:
"We have 3 developers using AI agents for ~60% of implementation. Estimate this feature."
Best Practices
- Start with a single task to calibrate before moving to batch mode
- Feed back actual completion times to improve the calibration system
- Use "instant mode" for quick T-shirt sizing without full PERT analysis
- Be explicit about team composition and agent usage percentage
Common Pitfalls
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
Related Skills
@sprint-planning- Sprint planning and backlog management@project-management- General project management workflows@capacity-planning- Team velocity and capacity planning
Additional Resources
Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
FAQ
Why does the tool ask if the team uses AI?
Because work time changes depending on whether AI assists or not. Knowing this makes the estimate more accurate.
What are 'confidence intervals'?
These are time ranges that indicate the probability of the task being completed. For example, a 90% interval means there's a 90% chance of finishing within that timeframe.
How does the tool get better over time?
It learns from the actual times tasks took to complete. This information helps adjust calculations for the future.
Details
Original description by the author
Estimate AI-assisted and hybrid human+agent development work with research-backed PERT statistics and calibration feedback loops
Popularity
- GitHub stars
- 48k
- Ranking position
- #3900
- License
- MIT
- Updated
- 10/15/2026
Comments
- …
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