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 agentmods add skills/cbrock84/headcount/business-intelligencenpx skills add cbrock84/headcount --skill business-intelligencegit 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/business-intelligence)<a href="https://agentmods.dev/skills/cbrock84/headcount/business-intelligence"><img src="https://agentmods.dev/badge/skills/cbrock84/headcount/business-intelligence.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00073 | $0.00805 |
| Opus 5 | $0.00036 | $0.00402 |
| Sonnet 5 | $0.00015 | $0.00161 |
| Haiku 4.5 | $0.00007 | $0.00081 |
Grade A, and why
business-intelligence 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 yesterday.
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.
Business intelligence
Most organizations have too many dashboards and too little insight. The two are related: when everything is measured, nothing is watched.
Start from the decision
Every report answers one question for one audience who can act on it. Before building, name the decision it informs and what a viewer would do differently based on it.
If nothing would change, do not build it. That single filter removes most dashboard requests, and the ones surviving it get used.
Metric trees
Structure metrics as a tree, not a list. One primary outcome at the top, decomposed into the drivers that mathematically produce it, each decomposed again.
Revenue = customers × average value. Customers = new + retained. New = traffic × conversion. And so on.
This does two things a metric list cannot: when the top number moves, you can walk down to find where; and it makes clear which metrics are levers and which are outcomes. Teams should be measured on levers they control, not on outcomes they influence.
Dashboard design
- One screen, one question. Scrolling dashboards are several dashboards that were not separated.
- Lead with the answer — the primary number, its comparison, and whether that is good. A number with no comparison is not information.
- Comparison always: prior period, target, or cohort. Choose deliberately, because each tells a different story.
- Say what "good" is. A viewer who cannot tell whether 4.2% is good will not act.
- Annotate the anomalies. The spike everyone asks about should carry its explanation, or you will explain it every month.
- Cut the rest. Charts nobody uses cost attention on every visit and make the useful ones harder to find.
Self-serve
Self-serve works when the semantic layer is trustworthy and the questions are anticipated. It fails when people are handed raw tables and left to define metrics themselves — that produces confident wrong answers, which is worse than a queue.
Give governed metrics, curated datasets, and templates for common questions. Keep the raw layer for analysts.
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.
- yesterday Changed · +17 lines 937e923ffb82
- 5d ago First seen · 66 lines · 73 tokens per session scan A 92664a5c7f80
business-intelligence is a skill published in the GitHub repository cbrock84/headcount (1,247 stars, last pushed 2d ago), licensed MIT. It adds 73 tokens to every session and 805 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 2026-08-30.
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