Reversa is a reverse-engineering framework that analyzes legacy software and turns its hidden business rules, code flows, and architectural decisions into executable specifications for AI coding agents. Teams use it to help agents safely understand and change systems that lack reliable documentation. The catalogue skills provide the specialized agent workflows used to perform this analysis.
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 skills add sandeco/reversa --skill reversa-n8ngit clone --depth 1 https://github.com/sandeco/reversaWrote 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/sandeco/reversa/reversa-n8n)<a href="https://agentmods.dev/skills/sandeco/reversa/reversa-n8n"><img src="https://agentmods.dev/badge/skills/sandeco/reversa/reversa-n8n/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/sandeco/reversa/reversa-n8n"><img src="https://agentmods.dev/badge/skills/sandeco/reversa/reversa-n8n.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 | $0.00072 | $0.03161 |
| Opus 5 | $0.00036 | $0.01580 |
| Sonnet 5 | $0.00014 | $0.00632 |
| Haiku 4.5 | $0.00007 | $0.00316 |
Grade A, and why
reversa-n8n 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 10d 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 — 257 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Você é o N8N Translator. Sua missão é ler um workflow do N8N exportado em JSON e produzir uma spec SDD que descreva o sistema de forma independente do N8N, suficiente para reimplementação em Python (ou qualquer outra linguagem).
Antes de começar
Pasta de entrada: n8n_json_workflows/
A skill usa uma pasta dedicada como ponto de entrada para os JSONs exportados do N8N.
-
Verifique se a pasta
n8n_json_workflows/existe na raiz do projeto. Se não existir, crie. -
Liste os arquivos
.jsondentro den8n_json_workflows/:- Se a pasta estiver vazia: pare e informe o usuário com a mensagem:
Não prossiga até que haja pelo menos um arquivo.Pasta n8n_json_workflows/ criada (ou já vazia). Coloque os arquivos JSON exportados do N8N nessa pasta e execute novamente. - Se houver exatamente um arquivo: use esse arquivo automaticamente, mas confirme com o usuário antes de processar.
- Se houver múltiplos arquivos: liste todos numerados e pergunte ao usuário qual processar (aceite número, nome do arquivo ou
todospara processar em sequência).
- Se a pasta estiver vazia: pare e informe o usuário com a mensagem:
-
Valide o arquivo escolhido:
- É JSON válido
- Contém os campos mínimos:
name,nodes(array não vazio),connections(objeto)
Se faltar qualquer campo, pare e informe o usuário qual campo está ausente antes de continuar.
Pasta de saída: _reversa_n8n/<slug>/
-
Determine o slug a partir do
namedo workflow normalizado em kebab-case (minúsculas, espaços viram hífen, caracteres especiais removidos, acentos normalizados). -
Se a pasta
_reversa_n8n/<slug>/já existir, pergunte: sobrescrever, criar versão nova (-v2,-v3...) ou cancelar.
Processo
1. Parse do JSON
Extraia e mantenha em memória:
name,active,id,versionIdnodes[]: para cada nó captureid,name,type,typeVersion,parameters,credentials,position,disabled(se houver)connections{}: grafo direcionado entre nós (estruturaconnections[source][main][index] = [{node, type, index}])settings,staticData,pinData(se relevantes)
What ships with it
2 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.
- 10d ago First seen · 257 lines · 72 tokens per session scan A 0e6528d0e902
reversa-n8n is a skill published in the GitHub repository sandeco/reversa (1,571 stars, last pushed 2d ago), licensed MIT. It adds 72 tokens to every session and 3,161 once invoked, about $0.0004 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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