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 detection-and-monitoringgit 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/detection-and-monitoring)<a href="https://agentmods.dev/skills/cbrock84/headcount/detection-and-monitoring"><img src="https://agentmods.dev/badge/skills/cbrock84/headcount/detection-and-monitoring/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/detection-and-monitoring"><img src="https://agentmods.dev/badge/skills/cbrock84/headcount/detection-and-monitoring.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 | $0.00098 | $0.00943 |
| Opus 5 | $0.00049 | $0.00472 |
| Sonnet 5 | $0.00020 | $0.00189 |
| Haiku 4.5 | $0.00010 | $0.00094 |
Grade A, and why
detection-and-monitoring 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 — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Detection and monitoring
Incident response assumes someone noticed. Most organizations that respond well to incidents found out from a customer, a vendor, or an extortion note, and the gap between compromise and discovery is where nearly all of the damage accumulates.
Decide what to log by asking what you would need afterward
Work backwards from the questions an investigation asks: who authenticated, from where, and what did they then do. That points at a short list that matters far more than volume.
- Identity events — authentication success and failure, MFA changes, privilege grants, new API keys and tokens, consent grants to applications.
- Endpoint process activity — what ran, what spawned it, what it connected to.
- Administrative actions in the platforms that hold your data, especially permission and sharing changes.
- Network egress where you have it, and DNS, which is cheap and unusually informative.
Retention decides whether you can investigate at all. Intrusions are commonly discovered months after entry, so logs kept for thirty days answer none of the useful questions. Split it: a short hot window you can search fast, and a longer cold archive you can still reach.
Centralize, and make the copy hard to erase
Logs stored only on the system that produced them are logs the attacker controls. Ship them off the host as they are written, to a destination with different credentials from the systems it collects from — otherwise one compromised administrator account ends both the intrusion and the evidence of it.
Write detections for behavior, not for events
A single event is almost never an incident. What distinguishes an attacker is a sequence: authentication from a new location, followed by a mailbox rule creation, followed by a bulk download.
- Start from the techniques that actually apply to you. Coverage is a property of your own estate, not of a vendor's rule count.
- Detect the steps an attacker cannot skip — persistence, privilege escalation, credential access, and exfiltration — rather than the tools they might use, which change.
- High-signal detections available cheaply: inbox rules that forward or delete externally, new federation or identity-provider trust, disabled logging, impossible travel on administrative accounts, and mass file access by a single principal.
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 · 83 lines · 98 tokens per session scan A d9a7371f2d13
detection-and-monitoring is a skill published in the GitHub repository cbrock84/headcount (1,356 stars, last pushed 9d ago), licensed MIT. It adds 98 tokens to every session and 943 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.
Other skills, from other repositories
save
Save durable decisions, findings, plans, and implementation knowledge from the visible Codex conversation into a new or existing NeatContext context. Use only when the user explicitly invokes this skill or asks to preserve the current conversation as reusable context.
mode
Show or set NeatContext routing to auto, ask, or manual for Codex, with an optional default shared with every other NeatContext host. Use only when the user explicitly invokes this skill or clearly asks to change routing behavior.
status
Report the NeatContext context and routing mode active in Codex, including missing-file or stale-routing warnings. Use when the user asks which context is connected or explicitly invokes this skill.
list
List the local NeatContext Contexts available to Codex. Use when the user asks what contexts exist, what can be connected, or explicitly invokes this skill.
build-oxpecker-web-app
Build or modify an Oxpecker web application in idiomatic F#, using endpoint routing, functional EndpointHandler and EndpointMiddleware composition, ASP.NET Core metadata, and focused endpoint tests.
go
Compatibility entry for Visual Stack's former /vstack:go command. Runs the wireframe and UI review tool, now called review. Use only when the user invokes /vstack:go.