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 sales-compensation-and-territorygit 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/sales-compensation-and-territory)<a href="https://agentmods.dev/skills/cbrock84/headcount/sales-compensation-and-territory"><img src="https://agentmods.dev/badge/skills/cbrock84/headcount/sales-compensation-and-territory/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/sales-compensation-and-territory"><img src="https://agentmods.dev/badge/skills/cbrock84/headcount/sales-compensation-and-territory.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 | $0.00096 | $0.01015 |
| Opus 5 | $0.00048 | $0.00508 |
| Sonnet 5 | $0.00019 | $0.00203 |
| Haiku 4.5 | $0.00010 | $0.00102 |
Grade A, and why
sales-compensation-and-territory 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 8d 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 — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Sales compensation and territory
A compensation plan is the clearest statement a company makes about what it actually wants. Reps will optimize it precisely, including in the ways you did not intend, and that is not a character flaw — it is the plan working.
Size territories on potential, not on the current book
A territory built from existing accounts rewards whoever inherited the good one and guarantees the argument that follows. Build from addressable potential — accounts that fit, weighted by how many of them could plausibly buy — then check that each territory can support the quota you intend to put on it.
A quota a territory mathematically cannot carry is not a stretch goal, it is a resignation on a delay. Do that arithmetic before assigning, and expect to find one or two territories that fail it.
Rebalance on a known cadence, so it is a process rather than a punishment, and account for in-flight pipeline when accounts move.
Set quotas people hit often enough to believe
If most of the team misses, the plan has stopped motivating and started demoralizing; the number is noise and everyone knows it. If nearly everyone clears easily, you are paying above market for average performance.
A distribution where a solid majority reach target, with real upside above it, keeps the plan credible. Build the aggregate from the territories rather than dividing the company number by headcount — the second is how you end up with quotas nobody accepted.
Account for ramp explicitly for new hires rather than pretending a first quarter is a normal one.
Pay on the outcome you actually want, and keep it simple
- What you pay on should be the thing you want more of. Paying purely on new bookings gets you new bookings, including bad ones that churn.
- Consider what protects quality: margin or discount-adjusted credit, a clawback window on early churn, or paying on collected revenue rather than signed.
- Three components is usually the limit. A plan a rep cannot compute in their head does not change behavior, because they cannot see which action pays. Complexity in a comp plan is a design failure, not sophistication.
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.
- 8d ago First seen · 92 lines · 96 tokens per session scan A cd1f95ddd061
sales-compensation-and-territory is a skill published in the GitHub repository cbrock84/headcount (1,356 stars, last pushed 9d ago), licensed MIT. It adds 96 tokens to every session and 1,015 once invoked, about $0.0005 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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