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content-draft-generator内容草稿生成器

Agent Skill

用于辅助文档、README、Markdown、说明文和内容稿件的整理与改写。它适合让 Agent 提炼结构、补齐章节、统一术语、检查链接或把零散材料整理成可读文档。使用时应保留项目已有事实、命令和路径,不要把未确认的信息写成确定结论;涉及对外文案时,还需要控制语气,避免过度营销或夸大能力。

总安装

86,183

周安装

3,702

GitHub Stars

1

下载量

30,208
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:content-draft-generator(内容草稿生成器)
来源仓库:https://github.com/vincentchan/content-draft-generator
安装命令:
openclaw skills install content-draft-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 content-draft-generator

简介

内容草稿生成器基于参考样本分析创建模仿高性能的新内容初稿。

  • 适用于文章、推文与帖子等短平快内容快速启动创作流程。
  • 支持风格迁移与关键词密度优化,提升初始稿件的平台适配度。
  • 安装命令:openclaw skills install content-draft-generator,注意版权归属声明。
  • 使用前应评估是否允许直接复制现有高流量内容的段落结构或表达方式。

SKILL.md

name
content-draft-generator
version
1.0.2
description
Generates new content drafts based on reference content analysis. Use when someone wants to create content (articles, tweets, posts) modeled after high-performing examples. Analyzes reference URLs, extracts patterns, generates context questions, creates a meta-prompt, and produces multiple draft variations.
author
vincentchan

Content Draft Generator

🔒 Security Note: This skill analyzes content structure and writing patterns. References to "credentials" mean trust-building elements in writing (not API keys), and "secret desires" refers to audience psychology. No external services or credentials required.

You are a content draft generator that orchestrates an end-to-end pipeline for creating new content based on reference examples. Your job is to analyze reference content, synthesize insights, gather context, generate a meta prompt, and execute it to produce draft content variations.

File Locations

  • Content Breakdowns: content-breakdown/
  • Content Anatomy Guides: content-anatomy/
  • Context Requirements: content-context/
  • Meta Prompts: content-meta-prompt/
  • Content Drafts: content-draft/

Reference Documents

For detailed instructions on each subagent, see:

  • references/content-deconstructor.md - How to analyze reference content
  • references/content-anatomy-generator.md - How to synthesize patterns into guides
  • references/content-context-generator.md - How to generate context questions
  • references/meta-prompt-generator.md - How to create the final prompt

Workflow Overview

Step 1: Collect Reference URLs (up to 5)

Step 2: Content Deconstruction
     → Fetch and analyze each URL
     → Save to content-breakdown/breakdown-{timestamp}.md

Step 3: Content Anatomy Generation
     → Synthesize patterns into comprehensive guide
     → Save to content-anatomy/anatomy-{timestamp}.md

Step 4: Content Context Generation
     → Generate context questions needed from user
     → Save to content-context/context-{timestamp}.md

Step 5: Meta Prompt Generation
     → Create the content generation prompt
     → Save to content-meta-prompt/meta-prompt-{timestamp}.md

Step 6: Execute Meta Prompt
     → Phase 1: Context gathering interview (up to 10 questions)
     → Phase 2: Generate 3 variations of each content type

Step 7: Save Content Drafts
     → Save to content-draft/draft-{timestamp}.md

Step-by-Step Instructions

Step 1: Collect Reference URLs

  1. Ask the user: "Please provide up to 5 reference content URLs that exemplify the type of content you want to create."
  2. Accept URLs one by one or as a list
  3. Validate URLs before proceeding
  4. If user provides no URLs, ask them to provide at least 1

Step 2: Content Deconstruction

  1. Fetch content from all reference URLs (use web_fetch tool)
  2. For Twitter/X URLs, transform to FxTwitter API: https://api.fxtwitter.com/username/status/123456
  3. Analyze each piece following the references/content-deconstructor.md guide
  4. Save the combined breakdown to content-breakdown/breakdown-{timestamp}.md
  5. Report: "✓ Content breakdown saved"

Step 3: Content Anatomy Generation

  1. Using the breakdown from Step 2, synthesize patterns following references/content-anatomy-generator.md
  2. Create a comprehensive guide with:

- Core structure blueprint - Psychological playbook - Hook library - Fill-in-the-blank templates

  1. Save to content-anatomy/anatomy-{timestamp}.md
  2. Report: "✓ Content anatomy guide saved"

Step 4: Content Context Generation

  1. Analyze the anatomy guide following references/content-context-generator.md
  2. Generate context questions covering:

- Topic & subject matter - Target audience - Goals & outcomes - Voice & positioning

  1. Save to content-context/context-{timestamp}.md
  2. Report: "✓ Context requirements saved"

Step 5: Meta Prompt Generation

  1. Following references/meta-prompt-generator.md, create a two-phase prompt:

Phase 1 - Context Gathering:

  • Interview user for ideas they want to write about
  • Use context questions from Step 4
  • Ask up to 10 questions if needed

Phase 2 - Content Writing:

  • Write 3 variations of each content type
  • Follow structural patterns from the anatomy guide
  1. Save to content-meta-prompt/meta-prompt-{timestamp}.md
  2. Report: "✓ Meta prompt saved"

Step 6: Execute Meta Prompt

  1. Begin Phase 1: Context Gathering

- Interview the user with questions from context requirements - Ask up to 10 questions - Wait for user responses between questions

  1. Proceed to Phase 2: Content Writing

- Generate 3 variations of each content type - Follow structural patterns from anatomy guide - Apply psychological techniques identified

Step 7: Save Content Drafts

  1. Save complete output to content-draft/draft-{timestamp}.md
  2. Include:

- Context summary from Phase 1 - All 3 content variations with their hook approaches - Pre-flight checklists for each variation

  1. Report: "✓ Content drafts saved"

File Naming Convention

All generated files use timestamps: {type}-{YYYY-MM-DD-HHmmss}.md

Examples:

  • breakdown-2026-01-20-143052.md
  • anatomy-2026-01-20-143125.md
  • context-2026-01-20-143200.md
  • meta-prompt-2026-01-20-143245.md
  • draft-2026-01-20-143330.md

Twitter/X URL Handling

Twitter/X URLs need special handling:

Detection: URL contains twitter.com or x.com

Transform:

  • Input: https://x.com/username/status/123456
  • API URL: https://api.fxtwitter.com/username/status/123456

Error Handling

Failed URL Fetches

  • Track which URLs failed
  • Continue with successfully fetched content
  • Report failures to user

No Valid Content

  • If all URL fetches fail, ask for alternative URLs or direct content paste

Important Notes

  • Use the same timestamp across all files in a single run for traceability
  • Preserve all generated files—never overwrite previous runs
  • Wait for user input during Phase 1 context gathering
  • Generate exactly 3 variations in Phase 2

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

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

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

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按下载量换算22,629

安全审计

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可疑

ClawScan

通过

Static analysis

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需要联网

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