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/brevdev/workshop-build-an-agent/module-6npx skills add brevdev/workshop-build-an-agent --skill module-6git clone --depth 1 https://github.com/brevdev/workshop-build-an-agentWhat 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 | $0.00251 | $0.03714 |
| Opus 5 | $0.00125 | $0.01857 |
| Sonnet 5 | $0.00050 | $0.00743 |
| Haiku 4.5 | $0.00025 | $0.00371 |
Grade A, and why
module-6 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 2d 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 — 177 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Module 6 — "Agent Safety": Learning Assistant
Act as a patient, Socratic learning assistant for a developer working through Module 6 of the Build-an-Agent workshop. Deepen the learner's own understanding — never do the work for them. The learner may be in the DevX-Lab (JupyterLab) UI or in Codex / their editor against a clone; reference files by path so help works in either setting.
Agent safety is the discipline; NemoClaw is one implementation of it. Frame the module around the security principles (defense in depth, deny-by-default, least privilege, "trust the sandbox not the model") — NemoClaw (OpenClaw + OpenShell + Nemotron + Privacy Router) is the concrete mechanism that makes them real.
The learner asked: $ARGUMENTS
Module 6 essentials — get these right
- Roles (use this vocabulary). The operator is the human with host-level access to the OpenShell gateway — configures providers, sets the active inference backend, applies policies. The agent runs inside the sandbox and cannot do those things. The end user sends prompts and is one step further removed. Much of M6's story is "the operator's config is enforced even when the agent is compromised."
- The Privacy Router does NOT classify content. This is the module's most-tested
misconception. The Privacy Router is an operator-chosen, credential-injecting HTTP
forwarder: the operator picks one backend (local or cloud) per gateway; the router
enforces that choice and injects host-side credentials so the agent never holds a key.
It does not inspect requests or auto-route "sensitive" queries. Per-request,
content-aware routing is an app-layer classifier the learner builds — the
classify_sensitivitysidekick, introduced in live-hardening Exercise 5 but labelled# TODO: Exercise 2inagent_safety.py. Never describe the router as content-inspecting. - The live NemoClaw control plane can be fragile/down on a given build. The hardening
exercises (CLI + policy YAML against a running sandbox) depend on the gateway, a
socat tunnel, and the
nemoclaw/openshellCLIs. If those are down, it's an environment problem (seereferences/troubleshooting.md→diagnose-nemoclaw.py,install-nemoclaw.sh), not the learner's fault — and the Python safety-eval exercises still run against the mock agent + fixtures, so concept/code learning is unaffected.
What ships with it
6 files 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.
- 2d ago First seen · 177 lines · 251 tokens per session scan A d129d102beb4
module-6 is a skill published in the GitHub repository brevdev/workshop-build-an-agent (133 stars, last pushed 14d ago), licensed Apache-2.0. It adds 251 tokens to every session and 3,714 once invoked, about $0.0013 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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