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 account-based-marketinggit 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/account-based-marketing)<a href="https://agentmods.dev/skills/cbrock84/headcount/account-based-marketing"><img src="https://agentmods.dev/badge/skills/cbrock84/headcount/account-based-marketing/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/account-based-marketing"><img src="https://agentmods.dev/badge/skills/cbrock84/headcount/account-based-marketing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 79 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00098 | $0.00922 |
| Opus 5 | $0.00049 | $0.00461 |
| Sonnet 5 | $0.00020 | $0.00184 |
| Haiku 4.5 | $0.00010 | $0.00092 |
Grade A, and why
account-based-marketing 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 5d 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 — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Account-based marketing
Account-based marketing inverts the usual model: instead of generating leads and finding out which accounts they came from, you choose the accounts and work them. It is a good fit for a narrow set of businesses and an expensive mistake for the rest.
Qualify the model before adopting it
It works when deal sizes are large enough to justify per-account effort, the addressable market is small enough to enumerate, buying groups have several people, and sales cycles are long enough for sustained effort to compound.
It does not work when the deal size cannot carry the cost, when the market is too large to name, or when marketing and sales will not actually coordinate. That last one is the usual failure: the tooling gets bought, the account list gets built, and the program becomes a more expensive way to run the same campaigns.
Run the arithmetic first. Total program cost divided by the number of accounts, against expected deal value and a realistic win rate, tells you the tier structure you can afford — or that you cannot afford this at all.
Build the list from fit and evidence, then hold it still
Start from the accounts that already look like your best customers — not by revenue but by why they bought and whether they stayed. Add observable signals: hiring, technology in use, funding, regulatory pressure, a change in leadership.
Then commit. A list that churns quarterly cannot compound, and compounding is the only reason this model beats broad demand generation. Agree the list with sales and get their explicit acceptance, because a list sales does not believe in is a list sales will not work.
Map the buying group, not the contact
Purchases at this size are made by several people with different concerns: the person with the problem, the person with the budget, the person who will operate it, and whoever can veto on security, legal or procurement grounds.
Reaching one champion and mistaking that for account coverage is the most common structural error. Track how many roles you have reached within each account, and treat single-threading as a status that needs fixing rather than a warning to note.
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.
- 5d ago First seen · 83 lines · 98 tokens per session scan A e148fc6565ca
account-based-marketing is a skill published in the GitHub repository cbrock84/headcount (1,320 stars, last pushed 6d ago), licensed MIT. It adds 98 tokens to every session and 922 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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