From f164268f87e4399f60856c9bb1d34a4ef0d78dd1 Mon Sep 17 00:00:00 2001
From: tactino <18781106300@163.com>
Date: Tue, 27 Oct 2026 16:34:31 -0400
Subject: [PATCH] Home page: step-ledger, the step ledger as a package, linked
 from the boundary-faults section (en and zh)

---
 docs/index.md    | 8 ++++++++
 docs/index.zh.md | 6 ++++++
 2 files changed, 14 insertions(+)

diff --git a/docs/index.md b/docs/index.md
index c010a2b..3698e6e 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -153,6 +153,14 @@ trainer's own log. Such faults happen outside experiments too: under
 first reward of every episode after an environment's first, until 1.4
 ([E51](https://github.com/PlugRL/plugrl-server/tree/main/experiments/e51-episode-accounting)).
 
+The step ledger is now a package of its own,
+[step-ledger](https://github.com/PlugRL/step-ledger), for Gymnasium and
+Stable-Baselines3 with or without PlugRL. Wrap each environment in
+`LedgerEnv` and the vector env the trainer sees in `LedgerVectorEnv` (or
+`LedgerVecEnv` for Stable-Baselines3); after the run, `stepledger compare`
+names the environment, episode, step and field of the first difference. Each
+side adds a few microseconds per environment step.
+
 This is the paper *Detecting Silent Faults at the Environment-Trainer
 Boundary in Reinforcement Learning*, accepted to the CoRL 2026 Workshop on
 Everything Beneath the Policy ([PDF](/assets/silent-faults-webp2026.pdf);
diff --git a/docs/index.zh.md b/docs/index.zh.md
index a1d0338..4259564 100644
--- a/docs/index.zh.md
+++ b/docs/index.zh.md
@@ -121,6 +121,12 @@ Hopper 和 Pusher 见 E56、E58）。在环境端记的回合记录，抓到了
 环境从第二个回合起都会丢掉回合的第一个奖励，直到 1.4 才修好
 （[E51](https://github.com/PlugRL/plugrl-server/tree/main/experiments/e51-episode-accounting)）。
 
+步账本现在单独做成了一个包 [step-ledger](https://github.com/PlugRL/step-ledger)，Gymnasium
+和 Stable-Baselines3 都能用，用不用 PlugRL 都行。给每个环境包一层 `LedgerEnv`，给训练端看到的
+向量环境包一层 `LedgerVectorEnv`（Stable-Baselines3 用 `LedgerVecEnv`）；跑完后
+`stepledger compare` 会指出第一处不一致在哪个环境、哪个回合、哪一步、哪个字段。每一侧每个环境步
+只多几微秒。
+
 这部分内容是论文 *Detecting Silent Faults at the Environment-Trainer Boundary in
 Reinforcement Learning*，已被 CoRL 2026 Workshop on Everything Beneath the Policy 录用
 （[PDF](/assets/silent-faults-webp2026.pdf)；[引用方式](#citing)）。