What is humanizer-zh?

A Chinese writing guide for reducing machine-like phrasing, checking AI-writing signals, and revising text in depth.

It is for rewriting Chinese social, general, or academic text and reviewing its style.

It helps make Chinese text sound more natural and can identify passages that appear machine-generated.

humanizer-zh — Skill for Claude Code by SummerSec

Install

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.

Any agent

npx skills add SummerSec/SumSec-Skills --skill humanizer-zh

Clone the repo

git clone --depth 1 https://github.com/SummerSec/SumSec-Skills

Made for: Claude Code.

Or install writing-zh, the plugin that ships this one along with the rest of its 2 skills.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/summersec/sumsec-skills/humanizer-zh/github.svg)](https://agentmods.dev/skills/summersec/sumsec-skills/humanizer-zh)

Your own site

<a href="https://agentmods.dev/skills/summersec/sumsec-skills/humanizer-zh"><img src="https://agentmods.dev/badge/skills/summersec/sumsec-skills/humanizer-zh/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/summersec/sumsec-skills/humanizer-zh"><img src="https://agentmods.dev/badge/skills/summersec/sumsec-skills/humanizer-zh.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 89 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 2,853 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

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	$0.00089	$0.02853
Opus 5	$0.00044	$0.01426
Sonnet 5	$0.00018	$0.00571
Haiku 4.5	$0.00009	$0.00285

Measured 5d ago against content hash 93cbfe270088, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

humanizer-zh 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 5d ago.

The scan reads SKILL.md. This mod also ships 7 executable files (scripts/academic_cn.py, scripts/compare_cn.py, scripts/detect_cn.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

writing-zh/skills/humanizer-zh/SKILL.md · 191 lines

How it starts

The opening of the file, as written. The whole thing — 191 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Humanizer-zh：中文 AI 文本去痕（CLI + 深度指南）

能力概览

本地 CLI（scripts/，humanize-chinese，MIT）：检测、改写、对比、风格与学术降重。
深度指南：对话内精修或 CLI 后的语义润色；识别与归类模式时必须对照 references/pattern-catalog.md。

路径选择： 需要分数、批量、--seed 复现 → 用 CLI。只能对话改写或需维基式细颗粒度核对 → 深度指南。CLI 完成后可再跑 detect_cn.py -s 复核。深度指南默认含「反 AI 审查」多步交付（见「处理流程」）。

本地 CLI 工具

要求 Python 3。在任意工作目录执行时，用 ${CLAUDE_SKILL_DIR} 定位脚本；若当前环境不支持该变量，则先进入本 skill 根目录（与 scripts/ 同级）。

# 检测（20+ 维度，0-100 分）
python "${CLAUDE_SKILL_DIR}/scripts/detect_cn.py" text.txt
python "${CLAUDE_SKILL_DIR}/scripts/detect_cn.py" text.txt -v          # 详细 + 最可疑句子
python "${CLAUDE_SKILL_DIR}/scripts/detect_cn.py" text.txt -s          # 仅评分
python "${CLAUDE_SKILL_DIR}/scripts/detect_cn.py" text.txt -j          # JSON 输出

# 改写
python "${CLAUDE_SKILL_DIR}/scripts/humanize_cn.py" text.txt -o clean.txt
python "${CLAUDE_SKILL_DIR}/scripts/humanize_cn.py" text.txt --scene social -a
python "${CLAUDE_SKILL_DIR}/scripts/humanize_cn.py" text.txt --style xiaohongshu

# 风格转换
python "${CLAUDE_SKILL_DIR}/scripts/style_cn.py" text.txt --style zhihu -o out.txt

# 前后对比
python "${CLAUDE_SKILL_DIR}/scripts/compare_cn.py" text.txt --scene tech -a

# 学术论文 AIGC 降重
python "${CLAUDE_SKILL_DIR}/scripts/academic_cn.py" paper.txt -o clean.txt --compare
python "${CLAUDE_SKILL_DIR}/scripts/academic_cn.py" paper.txt -o clean.txt -a --compare

评分量表

分数	等级	含义
0-24	LOW	基本像人写的
25-49	MEDIUM	有些 AI 痕迹
50-74	HIGH	大概率 AI 生成
75-100	VERY HIGH	几乎确定是 AI

Read the full file on GitHub · 191 lines

Files

What ships with it

27 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

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.

5d ago First seen · 191 lines · 89 tokens per session scan A 93cbfe270088

Subscribe to this mod's changes

humanizer-zh is a skill published in the GitHub repository SummerSec/SumSec-Skills (8 stars, last pushed 24d ago), licensed Apache-2.0. It adds 89 tokens to every session and 2,853 once invoked, about $0.0004 per session on Opus 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 2026-09-03.

Writing and docs dsh-plugin

dsh-sdk-upgrade

Safely select and install a compatible official @deepseek-ai SDK release for dsh plugin projects (dsh-web, dsh-trading, and similar monorepos) from npm using an isolated worktree, explicit cohort review, CI-equivalent validation, and controlled rollout — including syncing the project's declared DSH host-version floor…

zhu1090093659/dsh-web · 176 tokens

dsh-web-sdk-compatibility

Adapt and repair dsh-web after an approved official @deepseek-ai SDK/runtime cohort is selected or installed. Compare public API, type, service-injection, module-table, protocol, and behavior changes; map every change to repository consumers; implement the smallest fixes and durable compatibility contracts; handle…

zhu1090093659/dsh-web · 107 tokens

ov-experience-memory

Retrieve and apply OpenViking Experience memories through the Agent runtime's generic OpenViking search and read tools. Use before or during executable, multi-step, or tool-based work such as coding, file or data changes, configuration, deployment, workflow execution, and failure recovery when prior operational…

volcengine/OpenViking · 78 tokens

audit-playbook

A code-security audit playbook covering source-code review, runtime checks, software dependencies, deployment settings, and AI-agent security risks.

SeaOf0/dsh-redteam-model · 155 tokens

x64dbg-reversing

Perform dynamic reverse engineering and debugging using X64dbg/X32dbg through natural language commands powered by X64dbg MCP. Use this skill whenever the user wants to: debug executables, analyze program behavior at runtime, set breakpoints, inspect memory and registers, trace execution flow, bypass anti-debug…

SeaOf0/dsh-redteam-model · 144 tokens

ctf-playbook

A playbook for solving capture-the-flag challenges, where competitors find a hidden proof string called a flag.

SeaOf0/dsh-redteam-model · 367 tokens

humanizer-zh