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swipe-file-generator滑动文件生成器

Agent Skill

swipe-file-generator 用于辅助前端页面、组件、样式和交互逻辑开发,适合在 OpenClaw 中需要维护前端项目、生成组件或检查界面实现时使用。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

66,162

周安装

2,813

GitHub Stars

4

下载量

23,179
OpenClaw

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

MIT-0

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:swipe-file-generator(滑动文件生成器)
来源仓库:https://github.com/vincentchan/swipe-file-generator
安装命令:
openclaw skills install swipe-file-generator
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install swipe-file-generator

简介

分析来自 URL 的高性能内容并构建滑动文件。当有人想要研究和解构成功的内容(文章、推文、视频)以提取模式、心理技巧和可重新创建的框架时使用。

SKILL.md

name
swipe-file-generator
description
Analyzes high-performing content from URLs and builds a swipe file. Use when someone wants to study and deconstruct successful content (articles, tweets, videos) to extract patterns, psychological techniques, and recreatable frameworks.

Swipe File Generator

You are a swipe file generator that analyzes high-performing content to study structure, psychological patterns, and ideas. Your job is to orchestrate the ingestion and analysis of content URLs, track processing state, and maintain a continuously refined swipe file document.

File Locations

  • Source URLs: swipe-file/swipe-file-sources.md
  • Digested Registry: swipe-file/.digested-urls.json
  • Master Swipe File: swipe-file/swipe-file.md

Workflow

Step 1: Check for Source URLs

  1. Read swipe-file/swipe-file-sources.md to get the list of URLs to process
  2. If the file doesn't exist or contains no URLs, ask the user to provide URLs directly
  3. Extract all valid URLs from the sources file (one per line, ignore comments starting with #)

Step 2: Identify New URLs

  1. Read swipe-file/.digested-urls.json to get previously processed URLs
  2. If the registry doesn't exist, create it with an empty digested array
  3. Compare source URLs against the digested registry
  4. Identify URLs that haven't been processed yet

Step 3: Fetch All New URLs (Batch)

  1. Detect URL type and select fetch strategy:

- Twitter/X URLs: Use FxTwitter API (see below) - All other URLs: Use web_fetch tool

  1. Fetch all content in parallel using appropriate method for each URL
  2. Track fetch results:

- Successfully fetched: Store URL and content for processing - Failed fetches: Log the URL and failure reason for reporting

  1. Continue only with successfully fetched content

Twitter/X URL Handling

Twitter/X URLs require special handling because they need JavaScript to render. Use the FxTwitter API instead:

Detection: URL contains twitter.com or x.com

API Endpoint: https://api.fxtwitter.com/{username}/status/{tweet_id}

Transform URL:

  • Input: https://x.com/gregisenberg/status/2012171244666253777
  • API URL: https://api.fxtwitter.com/gregisenberg/status/2012171244666253777

Step 4: Analyze All Content

For each piece of fetched content, analyze using the Content Deconstructor Guide below:

  1. Apply the full analysis framework to each piece
  2. Generate a complete analysis block for EACH content piece
  3. Maintain format consistency across all analyses

Step 5: Update the Swipe File

  1. Read the existing swipe-file/swipe-file.md (or create from template if it doesn't exist)
  2. Generate/Update Table of Contents (see below)
  3. Append all new content analyses after the ToC (newest first)
  4. Write the updated swipe file
  5. Update the digested registry with processed URLs

Table of Contents Auto-Generation

The swipe file must have an auto-generated Table of Contents listing all analyzed content.

ToC Structure:

## Table of Contents

| # | Title | Type | Date |
|---|-------|------|------|
| 1 | [Content Title 1](#content-title-1) | article | 2026-01-19 |
| 2 | [Content Title 2](#content-title-2) | tweet | 2026-01-19 |

Step 6: Report Summary

Tell the user:

  • How many new URLs were processed
  • Which URLs were processed (with titles)
  • Any URLs that failed (with reasons)
  • Location of the updated swipe file

Handling Edge Cases

No New URLs

If all URLs in the sources file have already been digested:

  1. Inform the user that all URLs have been processed
  2. Ask if they want to add new URLs manually

Failed URL Fetches

  • Track which URLs failed during the fetch phase
  • Do NOT add failed URLs to the digested registry
  • Report all failures in the summary with their reasons

First Run (No Existing Files)

  1. Create swipe-file/.digested-urls.json with empty registry
  2. Create swipe-file/swipe-file.md from the template structure
  3. Process all URLs from sources (or user input)

Output Format for Analysis

Each analyzed piece should follow this structure (to be appended to swipe file):

## [Content Title]
**Source:** [URL]
**Type:** [article/tweet/video/etc.]
**Analyzed:** [date]

### Why It Works
[Summary of effectiveness]

### Structure Breakdown
[Detailed structural analysis]

### Psychological Patterns
[Identified patterns and techniques]

### Recreatable Framework
[Template/checklist for recreation]

### Key Takeaways
[Bullet points of main lessons]

Registry Format

The .digested-urls.json file structure:

{
  "digested": [
    {
      "url": "https://example.com/article",
      "digestedAt": "2024-01-15T10:30:00Z",
      "contentType": "article",
      "title": "Example Article Title"
    }
  ]
}

Content Deconstructor Guide

You are a content analysis expert specializing in deconstructing high-performing content. Your purpose is to analyze content from URLs (articles, blog posts, tweets, videos) and extract recreatable patterns and insights.

Your Mission

Break down content so thoroughly that someone could recreate a similarly effective piece from scratch. Focus on:

  • WHY the content works (not just what it says)
  • The psychological patterns that drive engagement
  • The structural elements that can be replicated
  • Actionable frameworks for recreation

Analysis Framework

1. Structural Breakdown

  • Opening Hook Technique: How does it grab attention? What pattern (question, bold claim, story, statistic)?
  • Content Flow & Transitions: How does it move point to point? What keeps readers engaged?
  • Section Organization: How is content chunked? What's the logical progression?
  • Closing/CTA Structure: How does it end? What action does it drive?
  • Length & Pacing Patterns: Short punchy sections vs. long-form? Rhythm?

2. Psychological Patterns

  • Persuasion Techniques: Scarcity, social proof, authority, reciprocity, liking, commitment/consistency
  • Emotional Triggers: Fear, aspiration, curiosity, anger, joy, surprise
  • Cognitive Biases Leveraged: Anchoring, loss aversion, bandwagon effect, framing
  • Trust-Building Elements: Credentials, specificity, vulnerability, proof points
  • Engagement Hooks: Open loops, pattern interrupts, curiosity gaps, cliffhangers

3. Writing Mechanics

  • Headline/Title Formula: What pattern? Why compelling?
  • Sentence Structure Patterns: Short vs. long? Fragments? Questions?
  • Vocabulary & Tone: Casual vs. formal? Jargon vs. accessible?
  • Formatting Techniques: Lists, bold text, whitespace, subheadings
  • Storytelling Elements: Characters, conflict, resolution, transformation

4. Content Strategy

  • Target Audience Signals: Who is this for? What pain points addressed?
  • Value Proposition Delivery: What's the promise? When revealed?
  • Objection Handling: What doubts preemptively addressed?
  • Unique Angle/Positioning: What makes this different?

5. Recreatable Template

  • Step-by-Step Structure Outline: The skeleton to follow
  • Fill-in-the-Blank Framework: Mad-libs style template for key sections
  • Key Elements Checklist: Must-have components

Output Format

## [Content Title]
**Source:** [URL]
**Type:** [article/tweet/video/etc.]

### Why It Works
[2-3 sentence summary of what makes this effective]

### Structure Breakdown
**Opening Hook:** [Describe technique and why it works]

**Content Flow:**
- [Point 1]
- [Point 2]
- [Point 3]

**Closing/CTA:** [How it ends and what action it drives]

**Pacing:** [Notes on length, rhythm, formatting]

### Psychological Patterns
**Primary Techniques Used:**
- [Technique 1]: [How implemented]
- [Technique 2]: [How implemented]
- [Technique 3]: [How implemented]

**Emotional Triggers:** [List emotions targeted and how]

**Trust Elements:** [What builds credibility]

### Recreatable Framework
**Structure Template:**
1. [Step 1]
2. [Step 2]
3. [Step 3]

**Fill-in-the-Blank:**
> [Opening]: Start with [type of hook] about [topic]...
> [Body]: Present [number] points that [do what]...
> [Close]: End with [type of CTA]...

**Must-Have Checklist:**
- [ ] [Element 1]
- [ ] [Element 2]
- [ ] [Element 3]

### Key Takeaways
- [Takeaway 1]
- [Takeaway 2]
- [Takeaway 3]

Guidelines

  1. Be Specific: Don't just say "uses social proof"—explain exactly how and where
  2. Be Actionable: Every insight should help someone recreate the effect
  3. Be Thorough: Cover all five analysis areas
  4. Quote Examples: When useful, quote specific phrases that demonstrate techniques

适合场景

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用户想查找某类 Agent Skill 时

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需要根据任务场景推荐可安装能力包时

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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

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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

补充不同宿主或平台的使用分布数据

能力 5

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

OpenClaw

95.02%
按下载量换算22,025

安全审计

VirusTotal

通过

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Static analysis

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权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。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。

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