Capacity Planner
Verified@1kalin
npx machina-cli add skill @1kalin/afrexai-capacity-planner --openclawCapacity Planner
Plan team and infrastructure capacity before it becomes a crisis.
What It Does
Takes your current workload data — team size, utilization rates, project pipeline, seasonal patterns — and builds a forward-looking capacity model. Flags bottlenecks 4-8 weeks before they hit.
When to Use
- Sprint planning feels like guesswork
- You're not sure if you can take on a new client/project
- Hiring decisions need data, not gut feel
- Infrastructure keeps getting slammed at predictable times
How to Use
Tell the agent about your situation:
"We have 8 engineers, 3 active projects, and a new client starting in March. Can we handle it?"
The agent will:
- Audit current load — Map people to commitments, calculate true utilization (not the number in your head)
- Model scenarios — What happens if the new project lands? What if two people quit? What if scope grows 30%?
- Flag risks — Identify single points of failure, overloaded roles, deadline clusters
- Recommend actions — Hire, redistribute, defer, or say no — with numbers behind each option
Capacity Framework
Utilization Bands
| Band | Rate | Meaning |
|---|---|---|
| 🟢 Green | <70% | Healthy buffer for unplanned work |
| 🟡 Yellow | 70-85% | Sustainable but tight |
| 🔴 Red | >85% | Burnout zone — something will slip |
Key Metrics
- Effective capacity = headcount × available hours × efficiency factor (typically 0.7-0.8)
- Demand pipeline = committed hours + probable hours (weighted by likelihood)
- Buffer ratio = (capacity - demand) / capacity — target 15-25%
- Time to constraint = weeks until demand exceeds capacity at current trajectory
Scenario Template
For each scenario, output:
- Headcount needed vs. available
- Skill gaps (specific roles/capabilities missing)
- Timeline risk (which deadlines move)
- Cost impact (overtime, contractors, lost revenue from saying no)
- Recommended action with confidence level
Output Format
CAPACITY SNAPSHOT — [Date]
━━━━━━━━━━━━━━━━━━━━━━━━━━
Team: [size] | Utilization: [%] | Buffer: [%]
Status: 🟢/🟡/🔴
CURRENT COMMITMENTS
- [Project A]: [X people, Y hours/week, end date]
- [Project B]: ...
PIPELINE (next 8 weeks)
- [Incoming work]: probability %, estimated load
- ...
RISKS
1. [Risk description + impact + timeframe]
2. ...
SCENARIOS
A) [Scenario]: [outcome summary]
B) [Scenario]: [outcome summary]
RECOMMENDATION
[Clear action with reasoning]
Tips
- Refresh capacity snapshots weekly during planning
- Track actual vs. predicted utilization to calibrate your efficiency factor
- Include non-project work (meetings, support, admin) — it's usually 20-30% of capacity
- Don't plan above 80% utilization. The remaining 20% isn't slack, it's where real work happens.
Go Deeper
Your capacity model is one piece of operational planning. For full business context packs covering finance, operations, and growth strategy across 10 industries:
→ AfrexAI Context Packs — $47 each, built by operators who've done the work.
→ AI Revenue Calculator — Find out where your business is leaking money (free tool).
→ Agent Setup Wizard — Get your AI agent configured for your specific business in 5 minutes.
Overview
Capacity Planner analyzes workload data—team size, utilization rates, project pipeline, and seasonal patterns—to build a forward-looking capacity model. It flags bottlenecks 4-8 weeks before they hit, helping you plan hiring, redistribution, or postponements with data-driven confidence.
How This Skill Works
You describe your situation to the agent. It audits current load by mapping people to commitments and calculating true utilization, then models scenarios such as new projects or staff changes, flags risks like overloaded roles, and recommends actions with quantified options.
When to Use It
- Sprint planning feels like guesswork
- You're not sure if you can take on a new client/project
- Hiring decisions need data, not gut feel
- Infrastructure keeps getting slammed at predictable times
- You want early warnings 4-8 weeks before bottlenecks
Quick Start
- Step 1: Audit current load — Map people to commitments and calculate true utilization.
- Step 2: Model scenarios — Consider impact of new projects, staff changes, or scope changes.
- Step 3: Flag risks and decide actions — Choose hires, redistributions, or deferments with quantified options.
Best Practices
- Refresh capacity snapshots weekly during planning
- Track actual vs predicted utilization to calibrate the efficiency factor
- Include non-project work (meetings, support, admin) — typically 20-30% of capacity
- Don't plan above 80% utilization; leave space for real work
- Use scenario modeling to stress-test plans with what-if analyses
Example Use Cases
- We have 8 engineers, 3 active projects, and a new client starting in March. Can we handle it?
- A software services firm assesses whether to staff up when a big client signs a contract using capacity snapshots.
- A SaaS product team forecasts capacity against quarterly sprints and predictable infrastructure spikes.
- A consulting team uses scenario modeling to decide on taking on two new projects while potential resignations loom.
- A development team uses the model to allocate resources and avoid overcommitment during peak seasons.
