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/workshop/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/workshop)<a href="https://agentmods.dev/skills/brevdev/workshop-build-an-agent/workshop"><img src="https://agentmods.dev/badge/skills/brevdev/workshop-build-an-agent/workshop/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/workshop"><img src="https://agentmods.dev/badge/skills/brevdev/workshop-build-an-agent/workshop.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00180 | $0.01513 |
| Opus 5.5 | $0.00072 | $0.00605 |
| Sonnet 5.5 | $0.00036 | $0.00303 |
| Haiku 4.5 | $0.00018 | $0.00151 |
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 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.
This is a copy
86% identical to video-copy-analyzer — 412 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.
How it starts
The opening of the file, as written. The whole thing — 73 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 + Landlock enabled |
| 7 | Harnesses & Skills | a pi-style harness + portable skills | $module-7 |
M1–M6 | 2–3 h | none main; opt. GPU (Ex4) |
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.
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 · +2 lines ff8c909ff526
- 21d ago Changed b3fe81dc14cf
- 1mo ago First seen · 71 lines · 180 tokens per session scan A bcbc2ebb3d8f
workshop 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 180 tokens to every session and 1,513 once invoked, about $0.0007 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 86% identical to video-copy-analyzer, differing in 412 lines, and is treated as a copy.
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