Capacity planning
Open-source Claude skills for Program Management in product development — charters, status reports, RAID logs, roadmaps, launch readiness, retros, postmortems, OKRs & more.
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Model team capacity against committed and planned demand to spot over-allocation and forecast what can realistically be delivered. Use when the user says "capacity planning", "do we have bandwidth", "are we over-allocated", "headcount vs. demand", "can we take on X", or needs to balance workload against available people.
SKILL.md
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Capacity Planning
Compare the work a team has signed up for against the capacity it actually has, and make over-allocation visible before it becomes slippage.
When to use
- Deciding whether the team can absorb new work.
- Planning a quarter/sprint allocation across people and workstreams.
- Diagnosing chronic over-commitment.
Inputs to gather
- People on the team and their availability (FTE %, PTO/holidays, on-call, shared allocations).
- The time horizon (sprint, month, quarter).
- Committed + requested work with rough sizing (see
estimation-sizing).
Process
- Compute gross capacity = people × working days in the horizon.
- Subtract overhead: meetings, support/on-call, PTO, ramp-up, and a realistic productivity factor (people aren't 100% project-billable — often ~60–80%). State the factor used.
- That's net available capacity.
- Sum committed demand (sized work) and compare to net capacity → surplus or deficit.
- Break down by person/role to catch individual over-allocation even when the team total looks fine (a single bottleneck skill blocks everything).
- If over-allocated, present options: cut/defer scope, add people, extend timeline, reduce overhead. Recommend one.
Output format
## Capacity — {{team}} · {{horizon}}
| Person | Avail % | Net days | Allocated days | Over/Under |
| --- | --- | --- | --- | --- |
**Team:** net capacity {{X}} vs. demand {{Y}} → **{{surplus/deficit}} of Z days**
**Assumptions:** productivity factor {{%}}, overhead {{...}}
**Recommendation:** {{cut / add / extend}}
Always state assumptions — capacity numbers are only as good as the overhead estimate behind them.