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 content-strategygit 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/content-strategy)<a href="https://agentmods.dev/skills/cbrock84/headcount/content-strategy"><img src="https://agentmods.dev/badge/skills/cbrock84/headcount/content-strategy/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/content-strategy"><img src="https://agentmods.dev/badge/skills/cbrock84/headcount/content-strategy.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 | $0.00070 | $0.00607 |
| Opus 5.5 | $0.00028 | $0.00243 |
| Sonnet 5.5 | $0.00014 | $0.00121 |
| Haiku 4.5 | $0.00007 | $0.00061 |
Grade A, and why
content-strategy 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 1mo 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 — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content strategy
Claim a territory, not a topic list
A content program works when a defined audience learns to expect a specific kind of value from you. That requires a territory narrow enough to own: the intersection of what you know unusually well, what your buyer needs help with, and what nobody else is covering properly.
Test it: could a competitor publish your last ten pieces without anyone noticing? If yes, you have a topic list.
Match format to job
Every piece should have one job, and the job dictates the format:
- Reach — a claim someone would repeat. Short, opinionated, self-contained.
- Trust — depth that demonstrates competence. Long, specific, evidenced.
- Conversion — content adjacent to the buying decision: comparisons, implementation guides, objection answers.
- Retention — content that makes existing customers better at the thing.
Programs skew heavily to reach and then wonder why the audience does not convert. Budget across all four deliberately.
Cadence beats volume
Pick a frequency sustainable at your worst week, not your best. Irregular publishing costs more than infrequent publishing, because the audience stops expecting you.
Platform commitment
Two platforms done properly beat five done adequately. Choose by where the audience already is and which format you can actually sustain — not by reach numbers.
Every piece should be planned with its derivatives: the long piece is the source, and the short-form versions are extracted, not written separately.
Measurement
Measure by job. Reach content is judged on reach; conversion content on conversion. Judging everything on traffic is why content programs drift toward the reach end and stay there.
Set a review point where a topic that is not working gets dropped. Content strategies fail by accumulation.
Sources
references/sources.md in this skill lists the outside authorities that settle the questions
here — what each one is authoritative for, and what you may do with it. Check them before
answering on anything they cover, and cite what you used. Most are free to read and not free
to reproduce; the use note on each is binding.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago Changed · +7 lines 4aaa07d6b76f
- 1mo ago First seen · 61 lines · 70 tokens per session scan A 0176714b571e
content-strategy is a skill published in the GitHub repository cbrock84/headcount (2,077 stars, last pushed 2d ago), licensed MIT. It adds 70 tokens to every session and 607 once invoked, about $0.0003 per session on Opus 5.5. 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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