headcount is an organization of independently installable Claude Code plugins, each grouping skills for a department such as finance, security, or demand generation. Claude Code users install the departments they need and invoke their skills for specialized work; the catalogue entries are skills and related agent tooling from that organization.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add cbrock84/headcount --skill capacity-and-demand-planninggit clone --depth 1 https://github.com/cbrock84/headcountWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/cbrock84/headcount/capacity-and-demand-planning)<a href="https://agentmods.dev/skills/cbrock84/headcount/capacity-and-demand-planning"><img src="https://agentmods.dev/badge/skills/cbrock84/headcount/capacity-and-demand-planning/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/cbrock84/headcount/capacity-and-demand-planning"><img src="https://agentmods.dev/badge/skills/cbrock84/headcount/capacity-and-demand-planning.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00066 | $0.00603 |
| Opus 5 | $0.00033 | $0.00302 |
| Sonnet 5 | $0.00013 | $0.00121 |
| Haiku 4.5 | $0.00007 | $0.00060 |
Grade A, and why
capacity-and-demand-planning scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Capacity and demand planning
This is operational throughput — how much work the organization can absorb. Allocating people
across projects is portfolio work, handled in pmo:portfolio-governance.
Forecast demand honestly
Separate the three components, because they need different treatment:
- Baseline — the steady rate, best estimated from your own history rather than from a plan.
- Trend — the direction, measured over enough periods to distinguish it from noise.
- Spikes — launches, seasonality, campaigns, incidents. Known spikes are a planning input; unknown ones are what headroom is for.
Forecast in the unit the work actually arrives in — tickets, orders, shipments, minutes of handling — not in revenue. Revenue divided by an average is a forecast of an average, and averages are where capacity planning goes to die.
Capacity is not headcount
Usable capacity is people multiplied by available hours multiplied by the fraction spent on the work in question. The last term is the one everyone omits and it is rarely above 70%: meetings, training, holiday, and the interruptions that come with the job are real.
Plan against realistic effective capacity. Planning at 100% guarantees the plan fails on its first ordinary week.
Queues tell you before the dashboard does
Utilization above roughly 80% makes wait times rise sharply and non-linearly — a system at 95% is not slightly slower than one at 85%, it is qualitatively worse. This is why "we have spare capacity on paper" coexists with a queue that never clears.
Watch the trend in queue age, not the queue length. A stable-length queue whose oldest item keeps getting older is a queue that is quietly failing its slowest customers.
Add capacity or fix flow
Before adding capacity, establish which it is:
- Genuine capacity shortfall — arrival rate exceeds service rate at reasonable utilization. Add capacity.
- Flow problem — rework, handoffs, waiting on another team, batching. Adding capacity here adds
cost and often makes throughput worse by increasing coordination. Send this to
operations:process-design.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 6d ago First seen · 60 lines · 66 tokens per session scan A c33213d4fb6f
capacity-and-demand-planning is a skill published in the GitHub repository cbrock84/headcount (1,335 stars, last pushed 6d ago), licensed MIT. It adds 66 tokens to every session and 603 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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