[Feature Request] A configurable "content quality gate" middleware for project documentation and release outputs

### 🥰 Description

At present, project outputs like release notes, wiki pages, and announcements largely rely on manual review, which can miss factual errors, sensitive terms, or noisy content.
I’d like to explore the possibility of an optional, configurable “content quality gate” layer that automatically performs a safety and factuality check before any text goes public.

### 🧐 Solution

I’m running an experimental project called **Publish Guardian**, originally designed as a verification middleware for AI-generated outputs. However, the same concept can be applied to general-purpose text—acting as a linting tool for trustworthiness.
The core logic: before content is published, a configurable rules engine performs fact-matching against sources, sensitive-word filtering, and compliance checks. The default policy is “block when uncertain”.

This could be integrated as a lightweight external step in documentation workflows (e.g., called from GitHub Actions or release scripts), reducing the risk of human oversight.

My work-in-progress prototype can be downloaded here:
https://coze-coding-project.tos.coze.site/coze_storage_7660514320345923599/infonet-project.tar_a0507e6a.gz?sign=1784534626-3c5f023abe-0-5a9c878c8b3dfbe3b039b5c2a6b511532954f586c838d238a30ade4258879d94

### 🚑 Other Information

Due to network constraints, I don’t have an online Telegram bot demo ready yet. I’m fully reachable via GitHub or at 1709125482@qq.com.
I’m not selling anything—I’m genuinely looking for the most brutally honest criticism: what would be the biggest pain point or risk of adding a “safety gate” layer to project communications? Any feedback is gold to me.

The issue names no repository files or tests. Start by reviewing the documentation workflows, GitHub Actions, and release scripts it identifies, then examine the linked Publish Guardian prototype. Done would require an agreed optional gate, supported checks and configuration, and a documented pass/fail policy before publication.

Written by the indexing model from the issue text.