Borrowing it
Nothing to install: this file belongs to brevdev/workshop-build-an-agent. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/brevdev/workshop-build-an-agent/main/.agents/skills/module-6/SKILL.mdgit clone --depth 1 https://github.com/brevdev/workshop-build-an-agentWrote 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/brevdev/workshop-build-an-agent/module-6)<a href="https://agentmods.dev/skills/brevdev/workshop-build-an-agent/module-6"><img src="https://agentmods.dev/badge/skills/brevdev/workshop-build-an-agent/module-6/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/brevdev/workshop-build-an-agent/module-6"><img src="https://agentmods.dev/badge/skills/brevdev/workshop-build-an-agent/module-6.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 | $0.00252 | $0.03734 |
| Opus 5.5 | $0.00101 | $0.01494 |
| Sonnet 5.5 | $0.00050 | $0.00747 |
| Haiku 4.5 | $0.00025 | $0.00373 |
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 17d 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 — 181 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. The learner builds a classifier that proposes a route; the lab does not connect it
to live routing — the
classify_sensitivitysidekick, introduced in live-hardening Exercise 5 but labelled# TODO: Exercise 2inagent_safety.py. Never describe the router as content-inspecting or switch shared gateway state per prompt. - 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→nemoclaw-health.sh,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.
- 17d ago Changed · +7 lines 0909263b941c
- 21d ago Changed · -3 lines · +1 tokens per session 0e5ff054f5f7
- 1mo 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 (151 stars, last pushed 16d ago), licensed Apache-2.0. It adds 252 tokens to every session and 3,734 once invoked, about $0.0010 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 2026-08-30.
Other skills, from other repositories
hr-onboarding
A new-hire onboarding plan as a single page — first week schedule, buddy + manager intro, learning track, equipment checklist, and "you're set when…" outcomes. Use when the brief mentions "onboarding", "new hire", "first week plan", or "入职".
book-mirror
Take any book (EPUB/PDF), produce a personalized chapter-by-chapter analysis. Each chapter is preserved in detail (The Chapter) and mirrored back to the reader's actual life (The Mirror) using brain context. The mirror observes and resonates — a friend pointing out parallels, NOT a consultant rearranging the reader's…
exam-forecast
Analyze past exams from the same professor to surface patterns — subject weighting, recurring issue-spot traps, favored hypo types, policy-vs-doctrine mix — and forecast likely emphases for the upcoming exam. Use when the user says "what's on the exam", "analyze past exams", "predict the exam", or shares past exams.
lean-formalize
Develop and verify a mathematical proof in Lean, continue an incomplete Lean project, or audit whether it proves the original statement. Connect actual inputs to intermediate lemmas, assemble the target theorem, check its transitive axioms, and provide a reproducible handoff. Use when Lean is requested or a specific…
eli5
Explain research, papers, or technical ideas in plain English with minimal jargon, concrete analogies, and clear takeaways. Use when the user says "ELI5 this", asks for a simple explanation of a paper or research result, wants jargon removed, or asks what something technically dense actually means.
deck-course-module
A course or workshop slide template with persistent learning goals, teaching pages, multiple-choice self-tests, and a wrap-up.