Plain Language Skill

plain-language

**English** ｜ [繁體中文](README.zh-TW.md)

Turn AI prose that needs three reads into prose that needs one — without changing what it says.

**Before**

Following an evaluation of the current implementation, it was determined that the introduction of a completeness validation gate at the import-to-persistence transition point is feasible; however, as the source system provides only a snapshot of the most recent period and does not retain historical sequences, retrospective verification of this layer cannot be performed, and forward-only observation must therefore be adopted.

**After**

**Bottom line:** We can add the check, but we can only prove it works going forward — there's no history to test against.

• It sits between import and the database write: incomplete data doesn't get written.
• The source system only gives us the latest snapshot, with no history.
• No history means no backtest. We'd have to accumulate results after it ships.

**Detail:** source exposes latest period only (no historical sequence). Backtesting needs a different source.

Same facts, same constraints, same hedge. 78 words → 62, and the answer arrives in the first line.

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An Agent Skill for rewriting convoluted, jargon-stacked AI output and technical documents into plain language. It has **two separate rule sets** — one for Traditional Chinese, one for English — because the two languages fail in different ways. They are not translations of each other.

Works with [Claude Code](https://claude.com/claude-code), [OpenClaw](https://docs.openclaw.ai), and any environment that supports Agent Skills.

Why two rule sets

The two languages fail differently, so porting one language's rules onto the other doesn't work.

**Chinese** — the worst habit is the unbroken multi-idea sentence. Chinese has no clause markers and tolerates comma chains, so one breath can carry thirty-plus characters and three separate ideas. It also lets you drop the subject legally, s