← 返回 Skills 市场
jzocb

Writing Style Skill

作者 jzOcb · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
132
总下载
0
收藏
0
当前安装
1
版本数
在 OpenClaw 中安装
/install jz-writing-style-skill
功能描述
可复用的写作风格 Skill 模板。内置自动学习: 从你的修改中自动提取规则,SKILL.md 越用越准。 Fork 后改成你自己的风格。
使用说明 (SKILL.md)

Writing Style Skill(模板)

Fork 这个 skill,改成你的写作风格。内置自动学习,越用越准。


🎯 怎么用

  1. Fork / clone 这个 skill
  2. 把下面的风格规则改成你自己的
  3. 让 AI 用这个 skill 写内容
  4. 你改到满意 → 脚本自动学习你改了什么
  5. 下次 AI 写出来的就更像你

【0】Voice Dimensions(量化你的风格)

用 1-10 分定义你的风格维度。AI 比"写得自然一点"这种话更容易理解数字。

Dimension Score 你的说明
formal_casual ?/10 偏正式还是偏随意?
technical_accessible ?/10 技术深度?
serious_playful ?/10 严肃还是活泼?
concise_elaborate ?/10 简洁还是详细?
reserved_expressive ?/10 保守还是直接?

💡 不知道填什么? 先跑几次 AI 写作 → 你改 → 自动学习会帮你填。


【1】角色与读者

我是谁:

  • (填你的身份,比如:独立开发者,新晋 AI 爱好者)

读者是谁:

  • (填你的读者,比如:对 AI 感兴趣的技术人)

和读者的关系:

  • (比如:同行交流,不是教学)

【2】写作规则

基础规则

  • (填你的规则,比如:不用"深入探讨"、段落要短、要有具体数字)

禁止词

  • (AI 爱用但你不喜欢的词,比如:值得注意的是、综上所述、本文将介绍)

句式偏好

  • (你喜欢的句式,比如:结论前置、不要学术导语)

💡 不需要一开始就写完。 这些规则会通过你的修改自动积累。 跑完 10 次写作→修改循环后,这里会长出几十条精准规则。


【3】格式规范

平台适配

平台 格式要求
X/Twitter 不渲染 markdown,用纯文本
小红书 emoji 多、分段短
博客 标准 markdown
(你的平台) (你的要求)

🔄 自动学习(内置)

这个 skill 会从你的修改中自动学习。不需要手动写规则。

工作原理

AI 用这个 skill 写初稿
    ↓
你改到满意
    ↓
脚本 diff 两版 → 提取你改了什么
    ↓
新规则自动写入这个 SKILL.md
    ↓
下次 AI 写出来就更像你

只需要两个数据点

  • original: AI 生成的第一版
  • final: 你最终确认的版本

中间改了几轮不管。在 Google Doc 里来回改了 10 次?无所谓,只比较首尾。

Agent 操作指南

写完内容后:

python3 scripts/observe.py record-original \x3Cfile> --account \x3C账号> --content-type \x3C类型>

人类确认最终版后:

python3 scripts/observe.py record-final \x3Cfile> --match \x3Chash>

提取规则(手动或 cron 自动):

python3 scripts/improve.py auto --skill .

规则分级

级别 含义 处理方式
P0 高置信度(多次出现) 自动应用
P1 中置信度 人工确认
P2 低置信度(仅 1 次) 存档观察

安全

  • 每次更新前自动备份 SKILL.md
  • improve.py rollback 一键回滚
  • auto 模式只应用 P0

📊 CLI 参考

observe.py(零依赖纯 Python)

命令 功能
record-original \x3Cfile> 记录 AI 原稿
record-final \x3Cfile> --match \x3Chash> 记录最终版
pending 查看待配对
stats 统计

improve.py(需要 LLM CLI)

命令 功能
extract [--days 7] 提取改进建议
auto 提取 + 自动应用 P0
show 查看提案
apply \x3Cid> 应用提案
rollback 回滚

支持的 LLM CLI: claude(Claude Code)/ llm(pip install llm)/ IMPROVE_LLM_CMD 环境变量


📂 数据存储

~/clawd/memory/                    # OpenClaw
~/.claude/memory/                  # Claude Code
├── skill-runs/\x3Cskill-name>/
│   └── YYYY-MM-DD.jsonl          # 每日观察日志
├── skill-proposals/\x3Cskill-name>/
│   └── YYYYMMDD-HHMMSS.md       # 改进提案
└── skill-backups/\x3Cskill-name>/
    └── SKILL-YYYYMMDD-HHMMSS.md  # 自动备份

自动检测环境,不需要手动配置路径。


🚀 30 天预期

时间 预期效果
第 1 周 积累 3-5 次修改,生成第一批规则
第 2 周 10+ 条规则,AI 输出明显更像你
第 1 月 30+ 条规则,风格维度自动校准
持续 规则库稳定增长,新 pattern 自动捕捉
安全使用建议
What to check before installing or running: - Review the two scripts (observe.py, improve.py) yourself to ensure you understand what they write and where. They will save AI originals and your final edits to local log directories (by default under ~/clawd/memory or ~/.claude/.openclaw memory paths). - The scripts send excerpts of original/final text to whatever LLM CLI is available (claude/llm or a command you set with IMPROVE_LLM_CMD). Only configure trusted LLM tooling; content will be included in prompts to that service. - Backups exist, but the improve.py 'auto' mode and the 'apply' command will modify SKILL.md in-place. Do not enable unattended auto-apply or cron jobs unless you are comfortable with automatic updates; review proposals (show) before applying. - To limit risk: set SKILL_LOG_DIR and SKILL_BACKUP_DIR to a dedicated folder, run the scripts in a test environment first, and avoid pointing IMPROVE_LLM_CMD at untrusted binaries. Keep copies of your SKILL.md or use version control so you can inspect changes. Overall: the skill is internally coherent for its stated purpose, but it performs persistent local storage and uses external LLM CLIs — exercise the usual caution with where generated/edited content is stored and which LLM endpoints receive it.
功能分析
Type: OpenClaw Skill Name: jz-writing-style-skill Version: 1.0.0 The skill implements a 'self-improving' mechanism that automatically modifies its own instructions (SKILL.md) based on LLM analysis of user edits. While the logic in scripts/improve.py and scripts/observe.py appears aligned with the stated purpose, the use of subprocess.run to execute local LLM CLIs (like 'claude' or 'llm') and the ability to overwrite the skill's own markdown instructions create a significant attack surface for persistent prompt injection. A malicious 'final' version of a document could potentially trick the LLM into injecting harmful instructions into SKILL.md, which the agent would then execute in future sessions.
能力评估
Purpose & Capability
The name/description promise an auto-learning writing-style template; scripts/README/SKILL.md implement exactly that: recording original/final texts, diffing edits, calling an LLM to extract rules, and merging proposals into SKILL.md. The required operations (file I/O in user home, calling an LLM CLI) are coherent with the feature set.
Instruction Scope
Runtime instructions tell the agent/user to run python scripts that record drafts/finals and run an 'improve' flow. These scripts read and write files under user home (~/clawd, ~/.openclaw, ~/.claude or a configurable SKILL_LOG_DIR), and they send content (original/final excerpts up to several KB) to a local LLM CLI (claude/llm or a custom IMPROVE_LLM_CMD). This is expected for the task, but the skill will store copies of generated and human-edited content and will include that content in prompts to whatever LLM CLI is configured.
Install Mechanism
No external download/install spec is present (instruction-only install). The repo includes two Python scripts and docs; there is no remote URL or archive download. The code will be placed on disk as part of skill installation, which is normal for this type of skill.
Credentials
The skill declares no required env vars or credentials. Scripts accept optional env vars (SKILL_BASE_DIR, SKILL_LOG_DIR, SKILL_TARGET_PATH, SKILL_PROPOSAL_DIR, SKILL_BACKUP_DIR, IMPROVE_LLM_CMD). These are reasonable for configuring paths and the LLM command, but IMPROVE_LLM_CMD can point to any command — ensure it is set to a trusted CLI. No unrelated cloud credentials or secrets are requested.
Persistence & Privilege
always:false (good). The skill writes logs, proposals, backups, and can update SKILL.md in-place via improve.py. The 'auto' mode will generate proposals and (when used with auto-apply) will apply P0 rules automatically; combined with automated invocation (cron or an agent run), this could autonomously modify the skill file. That behavior matches the stated feature but is a capability you should be aware of and control.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install jz-writing-style-skill
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /jz-writing-style-skill 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
v1.0.0: 写作风格 Skill 模板,内置自动学习。Fork 后改成你的风格。
元数据
Slug jz-writing-style-skill
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Writing Style Skill 是什么?

可复用的写作风格 Skill 模板。内置自动学习: 从你的修改中自动提取规则,SKILL.md 越用越准。 Fork 后改成你自己的风格。 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 132 次。

如何安装 Writing Style Skill?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install jz-writing-style-skill」即可一键安装,无需额外配置。

Writing Style Skill 是免费的吗?

是的,Writing Style Skill 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Writing Style Skill 支持哪些平台?

Writing Style Skill 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Writing Style Skill?

由 jzOcb(@jzocb)开发并维护,当前版本 v1.0.0。

💬 留言讨论