workshop

A guide and router for the Build an Agent workshop, a seven-module course on creating AI agents and related practices. It explains the module order, prerequisites, topics, and how the modules connect.

In plain words
What is it for?
It helps choose modules, check what each one requires, navigate the course, and find lessons about retrieval-augmented generation (RAG), evaluation, training, safety, and agent skills.
Why use it?
It helps learners understand where to begin and which lesson covers a particular topic before they start working.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/brevdev/workshop-build-an-agent/workshop
Any agent
npx skills add brevdev/workshop-build-an-agent --skill workshop
Clone the repo
git clone --depth 1 https://github.com/brevdev/workshop-build-an-agent

Made for: Claude Code, Codex.

Per session 180 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,477 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 86% copy Near-identical to another mod in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00180 $0.01477
Opus 5 $0.00090 $0.00739
Sonnet 5 $0.00036 $0.00295
Haiku 4.5 $0.00018 $0.00148

Measured 2d ago against content hash bcbc2ebb3d8f, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

workshop 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.

Origin

This is a copy

86% identical to video-copy-analyzer — 410 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.agents/skills/workshop/SKILL.md · 71 lines

How it starts

The opening of the file, as written. The whole thing — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Build-an-Agent Workshop — Guide & Router

The entry point and map for the Build-an-Agent workshop. Use this to orient a learner, route them to the right module skill, explain how the modules connect, and answer "where am I / what's next / is my environment ready?" — without doing their work for them.

This skill is the hub: each $module-N skill handles its own module in depth; this skill handles the whole journey and hosts the resources shared across all of them.

Invoking the tutor: the learner reaches these skills by running codex (in a DevX-Lab JupyterLab terminal, or against a local clone) and typing $workshop for this overview or $module-N (1–7) for a specific module (or run /skills to pick one from a menu); setup is in the README's Learn with an AI tutor section. Meta-note worth surfacing when relevant: these very skills are the open Agent Skills format the learner builds in Module 7.

The learner asked: $ARGUMENTS

The seven-module arc

Each module adds a capability and a matching discipline. Detailed version in references/map.md.

# Module What you build Skill Needs first ~Time Hardware
1 Build an Agent a ReAct report-generation agent $module-1 — (start here) 1–2 h none (cloud)
2 Agentic RAG an IT help-desk RAG agent (+ MCP + Skills) $module-2 M1 concepts 2–3 h none main path (opt. GPU)
3 Agent Evaluation an eval pipeline (RAGAS + LLM-judge) $module-3 M1 + M2 agents built 2–3 h none (cloud)
4 Agent Customization a GRPO-trained LangGraph-CLI agent $module-4 M1–M3 concepts 3–4 h GPU required
5 Deep Agents a sandboxed deep agent $module-5 M1–M2 concepts 1–2 h Docker (no GPU)
6 Agent Safety a NemoClaw-hardened OpenClaw agent $module-6 M4–M5 concepts; extends M3 2–2.5 h Docker + kernel ≥ 5.13
7 Harnesses & Skills a pi-style harness + portable skills $module-7 M1–M6 2–3 h none main; opt. GPU (Ex4)

Read the full file on GitHub · 71 lines

Files

What ships with it

5 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.

Changes

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.

  1. 2d ago First seen · 71 lines · 180 tokens per session scan A bcbc2ebb3d8f

Subscribe to this mod's changes

workshop 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 180 tokens to every session and 1,477 once invoked, about $0.0009 per session on Opus 5. A static security scan graded it A with 0 findings. It is 86% identical to video-copy-analyzer, differing in 410 lines, and is treated as a copy.

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