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 incident-responsegit 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/incident-response)<a href="https://agentmods.dev/skills/cbrock84/headcount/incident-response"><img src="https://agentmods.dev/badge/skills/cbrock84/headcount/incident-response/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/incident-response"><img src="https://agentmods.dev/badge/skills/cbrock84/headcount/incident-response.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 | $0.00064 | $0.00834 |
| Opus 5.5 | $0.00026 | $0.00334 |
| Sonnet 5.5 | $0.00013 | $0.00167 |
| Haiku 4.5 | $0.00006 | $0.00083 |
Grade A, and why
incident-response 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 — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Incident response
Breach notification runs on statutory clocks, measured in hours in several regimes. Involve Legal & Risk and qualified counsel as soon as personal data may be involved — not after the technical work is done.
Decide it is an incident, and say so
The most expensive delay is the hour spent debating whether this is really an incident. Declare early; standing down a declared incident is cheap, and discovering an hour late that it was real is not.
Name an incident commander immediately. One person, coordinating, not doing the technical work. Everyone else has a defined job. Incidents fail on coordination far more than on technical capability.
Order of operations
1. Contain before investigating. Stop the bleeding: isolate the host, revoke the credential, disable the account, block the path. It is tempting to watch the attacker to learn more — do that only with a deliberate decision, not by default.
2. Preserve evidence while containing. Snapshot before you rebuild. Capture volatile state — memory, connections, running processes — before powering anything off. Rebuilding a compromised host destroys the only record of how they got in, and you will need it.
3. Establish scope. What was accessed, what was taken, when it started, and whether it is still happening. Assume the initial scope is understated; it usually is. Look for persistence and lateral movement before declaring containment.
4. Eradicate and recover. Remove the access, close the path, then restore. Rebuild from known good rather than cleaning in place — you cannot prove a cleaned host is clean.
Rotate every credential the attacker could have reached, not only the ones you know they used.
5. Watch after recovery. Re-entry is common. Monitor specifically for the path they used and its neighbors.
Communication
Keep one timeline as the single source of truth, updated as facts are established, with each entry timestamped and attributed. Incidents generate contradictory information at speed, and the timeline is what stops the same question being answered three ways.
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 618efd67adad
- 1mo ago First seen · 75 lines · 64 tokens per session scan A c80e69e714f0
incident-response is a skill published in the GitHub repository cbrock84/headcount (2,077 stars, last pushed 2d ago), licensed MIT. It adds 64 tokens to every session and 834 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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