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 compensation-and-levelinggit 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/compensation-and-leveling)<a href="https://agentmods.dev/skills/cbrock84/headcount/compensation-and-leveling"><img src="https://agentmods.dev/badge/skills/cbrock84/headcount/compensation-and-leveling.svg" alt="Measured on agentmods" 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 | $0.00075 | $0.00766 |
| Opus 5 | $0.00037 | $0.00383 |
| Sonnet 5 | $0.00015 | $0.00153 |
| Haiku 4.5 | $0.00007 | $0.00077 |
Grade A, and why
compensation-and-leveling 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 3d 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 — 75 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Compensation and leveling
Compensation touches employment law, pay transparency requirements, and equal pay obligations that vary by jurisdiction. Structural work here is fine; specific decisions about individuals should be reviewed by qualified counsel or an HR professional.
Leveling first
Pay structure without a leveling framework produces negotiated salaries, and negotiated salaries produce inequity that correlates with who negotiates hardest.
Define each level by scope and impact, not tenure or task list:
- What ambiguity can they handle — a defined task, a defined problem, an undefined problem, a problem nobody has identified?
- What is the blast radius of their decisions — their work, their team, the function, the company?
- What do they do for others: execute, contribute, guide, or set direction?
Levels must be distinguishable in a sentence. If two adjacent levels cannot be told apart by someone who does not know the people in them, they are one level.
Bands
For each level, benchmark against a market defined by the roles you actually compete with for candidates — not the whole industry, and not aspirational peers.
- Set a target position (at market, above, or below) and state it as policy rather than deciding case by case.
- Bands wide enough to allow growth within a level, narrow enough to mean something.
- Re-benchmark on a schedule. Markets move, and bands that do not move create compression that eventually costs more to fix than to prevent.
Compression and equity
Compression — new hires paid near or above tenured staff — is the predictable result of moving markets and static internal pay. It is corrosive because it is discovered, and it is always discovered.
Run a pay equity analysis on a schedule: pay by level, controlling for level and location, disaggregated by demographic. Where a gap exists, fix it directly rather than waiting for the next cycle. Findings here need qualified review before action.
Decisions
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.
- 3d ago First seen · 75 lines · 75 tokens per session scan A b39eeeeaf6b0
compensation-and-leveling is a skill published in the GitHub repository cbrock84/headcount (1,300 stars, last pushed 4d ago), licensed MIT. It adds 75 tokens to every session and 766 once invoked, about $0.0004 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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