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 customer-success-managementgit 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/customer-success-management)<a href="https://agentmods.dev/skills/cbrock84/headcount/customer-success-management"><img src="https://agentmods.dev/badge/skills/cbrock84/headcount/customer-success-management/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/customer-success-management"><img src="https://agentmods.dev/badge/skills/cbrock84/headcount/customer-success-management.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
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 →
- high Anti-Refusal · line 47 Skill instructs the agent to omit warnings, disclaimers, or ethical commentary. Stripping safety caveats hides risk from the user and is a common jailbreak preamble.Fix: Remove instructions that suppress warnings, disclaimers, or ethical commentary. Let the agent surface safety-relevant caveats to the user.
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 | $0.00085 | $0.01013 |
| Opus 5 | $0.00043 | $0.00507 |
| Sonnet 5 | $0.00017 | $0.00203 |
| Haiku 4.5 | $0.00009 | $0.00101 |
Grade A, and why
customer-success-management 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.
Customer success management
This is the motion that keeps accounts, as distinct from diagnosing why they leave — for the
churn analysis itself, see revenue:retention. The failure this discipline exists to prevent is
finding out at renewal.
Segment coverage before hiring anyone
Coverage is a cost decision and it should be made explicitly rather than by whoever shouts.
- Named coverage for accounts where the revenue justifies a person and the relationship is genuinely complex. Fewer accounts per person than instinct suggests — a manager with sixty accounts is running a queue, not a relationship.
- Pooled coverage for the middle: a team owning a segment, working from signals rather than from a calendar.
- Programmatic coverage for the long tail: in-product guidance, lifecycle messaging, and self-service. This is not a lesser tier, it is the only one that scales, and it usually deserves more investment than it gets.
Assign by what the account needs, not only by what it pays. A large account that is live, stable and happy needs less than a small one mid-implementation.
Build a health score that predicts something
Most health scores are a weighted average of whatever was available, colored red to green, and trusted by nobody. A useful one is built backwards: take accounts that churned and accounts that renewed, and find what actually differed six months out.
- Usage depth and breadth — how many people, how often, how many of the things they bought.
- Trajectory over level. An account at 60% of expected usage and rising is healthier than one at 90% and falling. Level tells you where they are; direction tells you where they are going.
- Relationship coverage — how many people you know, and whether your only contact is the person who bought.
- Support and escalation history, weighted by severity rather than volume.
Validate it against outcomes and recalibrate. A score that did not predict last year's churn should not be steering this year's attention.
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 · 85 tokens per session scan A bb94e1adc60b
customer-success-management is a skill published in the GitHub repository cbrock84/headcount (1,356 stars, last pushed 9d ago), licensed MIT. It adds 85 tokens to every session and 1,013 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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