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 dewtech-technologies/dare-method --skill dare-reversegit clone --depth 1 https://github.com/dewtech-technologies/dare-methodWrote 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/dewtech-technologies/dare-method/dare-reverse)<a href="https://agentmods.dev/skills/dewtech-technologies/dare-method/dare-reverse"><img src="https://agentmods.dev/badge/skills/dewtech-technologies/dare-method/dare-reverse/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/dewtech-technologies/dare-method/dare-reverse"><img src="https://agentmods.dev/badge/skills/dewtech-technologies/dare-method/dare-reverse.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 | $0.00072 | $0.01681 |
| Opus 5.5 | $0.00029 | $0.00672 |
| Sonnet 5.5 | $0.00014 | $0.00336 |
| Haiku 4.5 | $0.00007 | $0.00168 |
Grade A, and why
dare-reverse 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 1mo 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 — 112 lines — stays where its author put it; the contents beside it link to each section on GitHub.
DARE Reverse Skill — Engenharia Reversa (Fase 0)
Equivalente no terminal:
dare reverse --ai· extração híbrida AST:dare reverse --deep --ast
Você é o agente da Fase 0 (brownfield) do método DARE no Antigravity. Esta skill é a
camada semântica da engenharia reversa: roda depois do comando dare reverse, que já
varreu o código e gerou os esqueletos determinísticos. Sua função é preencher as inferências
que o CLI não faz: propósito, domínio, responsabilidades e os diagramas de fluxo
("como a coisa funciona").
Pré-requisito: o comando
dare reverseprecisa ter rodado antes (geraDARE/IDEIA.md,DARE/REVERSE/module-*.mdeDARE/REVERSE/reverse-facts.json). Se não existirem, peça ao usuário para rodardare reverseprimeiro.
Quando usar esta skill
- O usuário quer entender / documentar um projeto legado antes de adotar o DARE.
- Acabou de rodar
dare reversee os artefatos têm seções<!-- AGENT: ... -->em aberto. - O objetivo é gerar uma pré-arquitetura (
IDEIA.md) que depois viraDESIGN.md.
Marcação de confiança (obrigatória)
Ao preencher cada <!-- AGENT -->, marque cada afirmação com seu nível de confiança + evidência:
- 🟢 <claim>.+`arquivo:linha`— CONFIRMED: evidência direta no código.- 🟡 <claim>.+`arquivo:linha`— INFERRED: padrão/dedução; pode estar errado.- 🔴 <claim>. → ver gaps.md— GAP: não determinável pelo código.
Regra: só 🟢 com evidência direta; na dúvida, 🟡; sem base, 🔴 (registre em gaps.md). Os fatos
estruturais (caminho, LOC, deps) já vêm pré-marcados 🟢 pelo CLI — não os altere.
Passo a passo
1. Carregar os fatos (não re-varrer tudo)
- Leia
DARE/REVERSE/reverse-facts.json— fonte de fatos determinística (stack, módulos, LOC, grafo de dependências). Confie nela para o inventário; não reconte arquivos. - Por módulo, abra 2-5 arquivos representativos (entrypoints, controllers, services, models) — o suficiente para inferir responsabilidade e fluxo. Não leia o módulo inteiro.
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.
- 1mo ago First seen · 112 lines · 72 tokens per session scan A c5d27f3a94cb
dare-reverse is a skill published in the GitHub repository dewtech-technologies/dare-method (5 stars, last pushed 3mo ago), licensed MIT. It adds 72 tokens to every session and 1,681 once invoked, about $0.0003 per session on Opus 5.5. 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.
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