support-staffing-model
How many support agents does the queue actually need — Erlang C, computed, not 'tickets per agent' folklore. Use when staffing a support/CS team, defending headcount, or checking whether an SLA is mathematically possible with the current roster. Produces agent counts across load scenarios (with shrinkage), occupancy and average-wait numbers, and a real .xlsx — via the bundled zero-dependency script.
npx skills add mohitagw15856/pm-claude-skills --skill support-staffing-model --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Support Staffing Model Queues are counterintuitive: at high occupancy, one extra contact per hour explodes wait times, and "tickets ÷ tickets-per-agent" staffing walks teams straight into the cliff. Erlang C is the century-old math call centers run on; this skill runs it for you, honestly labelled. ## Required Inputs - **Contacts per hour** (peak hour, not daily average — queues die at peaks) and **average handle time** in minutes. - **The SLA** — "X% answered within Y seconds/minutes". If none exists, propose one before staffing to it. - **Shrinkage** — the fraction of paid time agents aren't available (meetings, breaks, training). Teams that skip this understaff by 30-40%; default 0.3. ## Output Format 1. **The staffing table** — for load scenarios (0.8×, 1×, 1.25×, 1.5×): agents on-queue, rostered headcount after shrinkage, achieved service level, average speed of answer, occupancy. 2. **The occupancy warning** — anywhere occupancy exceeds ~90%, say plainly: the SLA may hold while the team burns out; staff for the humans. 3. **The folklore contrast** — the naive tickets-per-agent number next to the Erlang answer, so the reader sees what the old method was hiding. 4. **Model li
- Required Inputs
- Output Format
- Programmatic Helper
- Quality Checks
- Anti-Patterns
python3 scripts/erlang_staffing.py plan staffing.xlsx --arrivals 120 --aht 6 --sla 0.8 --answer-in 60 --shrinkage 0.3
What does the support-staffing-model skill do?
How many support agents does the queue actually need — Erlang C, computed, not 'tickets per agent' folklore. Use when staffing a support/CS team, defending headcount, or checking whether an SLA is mathematically possible with the current roster. Produces agent counts across load scenarios (with shrinkage), occupancy and average-wait numbers, and a real .xlsx — via the bundled zero-dependency script.
How do I install it?
Run `npx skills add mohitagw15856/pm-claude-skills --skill support-staffing-model --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From mohitagw15856/pm-claude-skills, a repository with 1,255 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.