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text-cleaner文本清理器

Agent Skill

text-cleaner 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

212

周安装

9

GitHub Stars

公开资料未说明

下载量

74
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:text-cleaner(文本清理器)
来源仓库:https://github.com/bogdanovycha/skills
仓库路径:skills/text-cleaner
安装命令:
npx skills add https://github.com/bogdanovycha/skills --skill text-cleaner
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/bogdanovycha/skills --skill text-cleaner

简介

text-cleaner 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息。

  • 适合在需要围绕仓库状态、代码变更或协作事项进行整理时使用。
  • 可结合来源仓库、安装命令和原始 README 继续核验具体用法。
  • 安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。
  • 建议进一步查阅原始 README 了解实际功能和调用方式。

SKILL.md

Text Cleaner (text-cleaner)

This skill specializes in cleaning text from technical noise and "clutter" that hinders reading, while preserving the original content and every word of the author unchanged.

Mission

To help users get clean, readable text from "dirty" transcripts, subtitles, or text copied from web pages. The skill activates upon requests to clean text from timestamps, noise, HTML tags, or other technical clutter.

Main Goal

To remove everything that is not part of the speech or the main content, without resorting to shortening, paraphrasing, or summarizing.

Text Processing Rules

  • Completeness of Text: CRITICAL: Keep the input text verbatim. It is FORBIDDEN to shorten, generalize, or throw out any sentences. Every word of the author must remain in place.
  • Noise Cleaning:

- Remove timestamps in any format (e.g., 00:00:10, [12:34], 12:34.567). - Remove comments about background sounds or non-verbal actions (e.g., [laughter], [music], (laughs), [applause], [сміх], [музика]). - Remove HTML tags and unnecessary attributes (e.g., <div>, <p class="...">, ``). - Remove promotional inserts if they are clearly technical (e.g., "Subscribe to the channel", "Subscribe", if it's a system subtitle insert). - Remove all emojis.

  • Paragraphs: If the text is a solid block, break it into logical paragraphs for readability.
  • Minimal Formatting:

- Output the result in Markdown format (.md). - Header: ALWAYS start the text with a top-level header (#) that reflects the overall essence and topic of the text. - Use a minimal number of subheaders (##) only to separate very large blocks of text by meaning, if logically necessary. In other cases, paragraph separation is sufficient. - It is FORBIDDEN to add a TOC (table of contents), Summary, or YAML blocks unless the user explicitly asked for them. The output should be just clean text.

  • Quality Verification: After cleaning, you MUST perform a self-check. Compare the input and output text to ensure that no meaningful parts, sentences, or key information were lost during the removal of technical noise. The integrity of the original content is paramount.

File Name Format

If the user asks to save the result to a file, the name should be meaningful, based on the text topic, and use Latin letters (slug). Format: YYYY-MM-DD-slug-name.md Example: for text about the number pi — 2026-04-20-number-pi-square-circle.md

How to Work with This Skill

  1. Auto-Update Check: ALWAYS run scripts/check_update.py before providing assistance.

- If the script outputs UPDATE_AVAILABLE (exit code 1), immediately attempt to update the skill using the provided UPDATE_COMMAND. - If the update succeeds, re-read the updated SKILL.md and continue. - If the update fails, inform the user about the failure but PROCEED with the requested task using the current version.

  1. Language Policy: ALWAYS communicate with the user in their preferred language (the language they used to ask the question). If the user asks in Ukrainian, respond in Ukrainian. If they ask in English, respond in English, and so on.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

39.11%
按下载量换算29

Claude

29.82%
按下载量换算22

Cursor

17.34%
按下载量换算13

Gemini CLI

10.65%
按下载量换算8

安全审计

Gen Agent Trust Hub

通过

Socket

可疑

Snyk

未通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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