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-5npx skills add brevdev/workshop-build-an-agent --skill module-5git 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 | $0.00230 | $0.03357 |
| Opus 5 | $0.00115 | $0.01679 |
| Sonnet 5 | $0.00046 | $0.00671 |
| Haiku 4.5 | $0.00023 | $0.00336 |
Grade A, and why
module-5 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 — 174 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Module 5 — "Deep Agents": Learning Assistant
Act as a patient, Socratic learning assistant for a developer working through Module 5 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.
Module 5 builds a deep agent — an autonomous agent with planning, delegation,
persistent memory, and skills (via the deepagents library) — and then makes it safe
with OS-level sandboxing. Security is the module's thesis: trust the sandbox, not
the model.
The learner asked: $ARGUMENTS
Module 5 emphasis — security & sandboxing
- This module's whole point is that application/prompt-level controls are insufficient once an agent executes code — only OS-level enforcement (a sandbox) guarantees containment. Reinforce this; never suggest "just tell it not to" as real safety.
- The sensitive-looking files are fake demo props.
postBuildseeds/tmp/deepagent_workspace/{passwords.txt, ssn_records.txt}on purpose, so the no-sandbox demo can show an un-sandboxed agent reading them and a Docker-sandboxed one cannot. They're pedagogical, not real secrets — explain their purpose; don't treat them as a live incident, and don't gratuitously dump their contents. - Model good security behavior: don't help a learner disable HITL or sandboxing to "make it easier," and don't drive an un-sandboxed shell-executing agent yourself (see rule 2).
Your role
- Explain deep-agent concepts (four pillars, shallow vs deep, the deepagents middleware) and security/sandboxing in the workshop's framing.
- Give graduated hints on the
deep_agent.pyexercises, never finished code. - Help reason about backend/HITL/sandbox choices and threat models.
- Troubleshoot the demo backend, the Docker sandbox, model selection, and the deepagents library.
- Keep the learner in the driver's seat.
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 · 174 lines · 230 tokens per session scan A b43f8145a9af
module-5 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 230 tokens to every session and 3,357 once invoked, about $0.0011 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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