2akouwu/reverify

重新验证

阻止你的AI编造事实。 它提出;确定性工具会将每一个主张与真实性对照进行核对，只有经过验证的才算数。

AI自信且常常出错：它发明API、结构字段、偏移量，或者什么 函数做到了，并且像事实一样说出来。重新验证使确定性工具成为评判者——模型 提出索赔，工具将其与实际工件核对，结果为已验证 / 被证据驳斥。模型从未能单独断言事实。

它今天做的两件事：

• 保持AI诚实 — 每一个结构性或行为性主张都经过核对 真理，不被信任，只有幸存的部分才成为事实（reverify verify，或MCP 你的代理已经联系过的服务器）。
• 防止你的AI上下文腐烂 — 代替有损自动摘要，reverify rollover 把会话交给一个文件，然后重新开始一个新文件，这样长时间的任务就不会漂移或需要 /clear。可使用 Claude 代码、Codex、Gemini CLI 和 OpenCode。

最难证明第一点的地方是二进制逆向工程，其中幻觉是 最差——所以这些数字就是从这里来的。

Reverify

Stop your AI from making things up. It proposes; deterministic tools check every claim against ground truth, and only what’s verified counts.

AI is confident and often wrong: it invents an API, a struct field, an offset, or what a function does, and says it like fact. Reverify makes a deterministic tool the judge — the model proposes a claim, the tool checks it against the actual artifact, and it comes back VERIFIED / REFUTED with evidence. The model never gets to assert a fact on its own.

Two things it does today:

• Keeps your AI honest — every structural or behavioral claim is checked against ground truth, not trusted, and only what survives becomes a fact (reverify verify, or the MCP server your agent already talks to).
• Keeps your AI’s context from rotting — instead of a lossy auto-summary, reverify rollover hands the session off to a file and starts a fresh one, so long tasks don’t drift or need /clear. Works in Claude Code, Codex, Gemini CLI and OpenCode.

The hardest place to prove the first point is binary reverse engineering, where hallucination is worst — so that’s where the numbers come from. On 71 real Windows system files the AI’s textbook answer was wrong 97% of the time; reverify caught every one and never accepted a wrong claim (0 of 71; the same gate runs in CI on Linux and macOS every push, and an independent aarch64 run found the same) (EXAMPLE.md, BENCHMARK.md; python benchmarks/prologue_prior.py).

The problem

Language models are great at reading code and unreliable at reverse engineering. Ask a