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 commands/lodetomasi/claude-code-training-lab/deploygit clone --depth 1 https://github.com/lodetomasi/claude-code-training-labWhat 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 | $0.00006 | $0.00165 |
| Opus 5 | $0.00003 | $0.00082 |
| Sonnet 5 | $0.00001 | $0.00033 |
| Haiku 4.5 | $0.00001 | $0.00016 |
Grade A, and why
deploy 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.
The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
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 · 26 lines · 6 tokens per session scan A 46706d772f78
deploy is a command published in the GitHub repository lodetomasi/claude-code-training-lab (2 stars, last pushed 6mo ago), with no licence file. It adds 6 tokens to every session and 165 once invoked, about $0.0000 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 2026-08-31.
Other commands, from other repositories
dare-blueprint
Gera somente DARE/BLUEPRINT.md a partir do DARE/DESIGN.md.
dare-dag-build
Regenera apenas o DARE/dare-dag.yaml a partir do DARE/BLUEPRINT.md já existente, sem refazer o blueprint nem as specs. Útil quando o BLUEPRINT mudou pouco mas você precisa que o grafo reflita o novo estado.
dare-dag-viz
Gera diagrama interativo .excalidraw a partir do dare-dag.yaml atual, com cores semânticas por complexidade e status visual das tasks.
dare-ax
Audita ou bootstrapa um projeto DARE com foco em Agent Experience (AX) — os sinais estruturados que agentes de código (Claude Code, Cursor, Antigravity) precisam para trabalhar sem refactor desnecessário.
dare-bugfix-design
Diagnostica bug em projeto existente e planeja correção cirúrgica via Método DARE. Gera DARE/DESIGN-Bugfix-[Nome].md com causa raiz, riscos de regressão e plano de ação mínimo.
dare-dag-runner
Wrapper agregador que cobre todo o ciclo do DAG num único comando: build do dare-dag.yaml (se necessário) → execução de todas as tasks via Ralph Loop → opcional visualização final em Excalidraw.