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Blog Draft

CommunityPopular
luongnv89
blog-draft

Draft a blog post from ideas and resources. Use when users want to write a blog post, create content from research, or draft articles. Guides through research, brainstorming, outlining, and iterative drafting with version control.

Overview

Publisherluongnv89
Repositoryclaude-howto
Skill nameblog-draft
Stars
41.5K
Forks
5.1K
Bundled files
2
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by luongnv89 on GitHub. Read the source before you install it.

Installation

Install the Blog Draft AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/luongnv89/claude-howto.git /tmp/claude-howto
mkdir -p .claude/skills
cp -r /tmp/claude-howto/03-skills/blog-draft .claude/skills/blog-draft
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Blog Draft in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Blog Draft on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Blog Draft is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

User Input

text
$ARGUMENTS

You MUST consider the user input before proceeding. User should provide:

  • Idea/Topic: The main concept or theme for the blog post
  • Resources: URLs, files, or references to research (optional but recommended)
  • Target audience: Who the blog post is for (optional)
  • Tone/Style: Formal, casual, technical, etc. (optional)

IMPORTANT: If the user is requesting updates to an existing blog post, skip steps 0-8 and start directly at Step 9. Read the existing draft file(s) first, then proceed with the iteration process.

Execution Flow

Follow these steps sequentially. Do not skip steps or proceed without user approval where indicated.

Step 0: Create Project Folder

  1. Generate a folder name using format: YYYY-MM-DD-short-topic-name

    • Use today's date
    • Create a short, URL-friendly slug from the topic (lowercase, hyphens, max 5 words)
  2. Create the folder structure:

    blog-posts/
    └── YYYY-MM-DD-short-topic-name/
        └── resources/
  3. Confirm folder creation with user before proceeding.

Step 1: Research & Resource Collection

  1. Create resources/ subfolder in the blog post directory

  2. For each provided resource:

    • URLs: Fetch and save key information to resources/ as markdown files
    • Files: Read and summarize in resources/
    • Topics: Use web search to gather up-to-date information
  3. For each resource, create a summary file in resources/:

    • resources/source-1-[short-name].md
    • resources/source-2-[short-name].md
    • etc.
  4. Each summary should include:

    markdown
    # Source: [Title/URL]
    
    ## Key Points
    - Point 1
    - Point 2
    
    ## Relevant Quotes/Data
    - Quote or statistic 1
    - Quote or statistic 2
    
    ## How This Relates to Topic
    Brief explanation of relevance
  5. Present research summary to user.

Step 2: Brainstorm & Clarify

  1. Based on the idea and researched resources, present:

    • Main themes identified from research
    • Potential angles for the blog post
    • Key points that should be covered
    • Gaps in information that need clarification
  2. Ask clarifying questions:

    • What is the main takeaway you want readers to have?
    • Are there specific points from the research you want to emphasize?
    • What's the target length? (short: 500-800 words, medium: 1000-1500, long: 2000+)
    • Any points you want to exclude?
  3. Wait for user responses before proceeding.

Step 3: Propose Outline

  1. Create a structured outline including:

    markdown
    # Blog Post Outline: [Title]
    
    ## Meta Information
    - **Target Audience**: [who]
    - **Tone**: [style]
    - **Target Length**: [word count]
    - **Main Takeaway**: [key message]
    
    ## Proposed Structure
    
    ### Hook/Introduction
    - Opening hook idea
    - Context setting
    - Thesis statement
    
    ### Section 1: [Title]
    - Key point A
    - Key point B
    - Supporting evidence from [source]
    
    ### Section 2: [Title]
    - Key point A
    - Key point B
    
    [Continue for all sections...]
    
    ### Conclusion
    - Summary of key points
    - Call to action or final thought
    
    ## Sources to Cite
    - Source 1
    - Source 2
  2. Present outline to user and ask for approval or modifications.

Step 4: Save Approved Outline

  1. Once user approves the outline, save it to OUTLINE.md in the blog post folder.

  2. Confirm the outline has been saved.

Step 5: Commit Outline (if in git repo)

  1. Check if current directory is a git repository.

  2. If yes:

    • Stage the new files: blog post folder, resources, and OUTLINE.md
    • Create commit with message: docs: Add outline for blog post - [topic-name]
    • Push to remote
  3. If not a git repo, skip this step and inform user.

Step 6: Write Draft

  1. Based on the approved outline, write the full blog post draft.

  2. Follow the structure from OUTLINE.md exactly.

  3. Include:

    • Engaging introduction with hook
    • Clear section headers
    • Supporting evidence and examples from research
    • Smooth transitions between sections
    • Strong conclusion with takeaway
    • Citations: All comparisons, statistics, data points, and factual claims MUST cite the original source
  4. Save the draft as draft-v0.1.md in the blog post folder.

  5. Format:

    markdown
    # [Blog Post Title]
    
    *[Optional: subtitle or tagline]*
    
    [Full content with inline citations...]
    
    ---
    
    ## References
    - [1] Source 1 Title - URL or Citation
    - [2] Source 2 Title - URL or Citation
    - [3] Source 3 Title - URL or Citation
  6. Citation Requirements:

    • Every data point, statistic, or comparison MUST have an inline citation
    • Use numbered references [1], [2], etc., or named citations [Source Name]
    • Link citations to the References section at the end
    • Example: "Studies show that 65% of developers prefer TypeScript [1]"
    • Example: "React outperforms Vue in rendering speed by 20% [React Benchmarks 2024]"

Step 7: Commit Draft (if in git repo)

  1. Check if in git repository.

  2. If yes:

    • Stage the draft file
    • Create commit with message: docs: Add draft v0.1 for blog post - [topic-name]
    • Push to remote
  3. If not a git repo, skip and inform user.

Step 8: Present Draft for Review

  1. Present the draft content to user.

  2. Ask for feedback:

    • Overall impression?
    • Sections that need expansion or reduction?
    • Tone adjustments needed?
    • Missing information?
    • Specific edits or rewrites?
  3. Wait for user response.

Step 9: Iterate or Finalize

If user requests changes:

  1. Note all requested modifications
  2. Return to Step 6 with the following adjustments:
    • Increment version number (v0.2, v0.3, etc.)
    • Incorporate all feedback
    • Save as draft-v[X.Y].md
    • Repeat Steps 7-8

If user approves:

  1. Confirm the final draft version
  2. Optionally rename to final.md if user requests
  3. Summarize the blog post creation process:
    • Total versions created
    • Key changes between versions
    • Final word count
    • Files created

Version Tracking

All drafts are preserved with incremental versioning:

  • draft-v0.1.md - Initial draft
  • draft-v0.2.md - After first round of feedback
  • draft-v0.3.md - After second round of feedback
  • etc.

This allows tracking the evolution of the blog post and reverting if needed.

Output Files Structure

blog-posts/
└── YYYY-MM-DD-topic-name/
    ├── resources/
    │   ├── source-1-name.md
    │   ├── source-2-name.md
    │   └── ...
    ├── OUTLINE.md
    ├── draft-v0.1.md
    ├── draft-v0.2.md (if iterations)
    └── draft-v0.3.md (if more iterations)

Tips for Quality

  • Hook: Start with a question, surprising fact, or relatable scenario
  • Flow: Each paragraph should connect to the next
  • Evidence: Support claims with data from research
  • Citations: ALWAYS cite sources for:
    • All statistics and data points (e.g., "According to [Source], 75% of...")
    • Comparisons between products, services, or approaches (e.g., "X performs 2x faster than Y [Source]")
    • Factual claims about market trends, research findings, or benchmarks
    • Use inline citations with format: [Source Name] or [Author, Year]
  • Voice: Maintain consistent tone throughout
  • Length: Respect the target word count
  • Readability: Use short paragraphs, bullet points where appropriate
  • CTA: End with a clear call-to-action or thought-provoking question

Notes

  • Always wait for user approval at outlined checkpoints
  • Preserve all draft versions for history
  • Use web search for up-to-date information when URLs are provided
  • If resources are insufficient, ask user for more or suggest additional research
  • Adapt tone based on target audience (technical, general, business, etc.)

Last Updated: August 4, 2026 Claude Code Version: 2.1.220 Sources:

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Blog Draft AI skill do?

Draft a blog post from ideas and resources. Use when users want to write a blog post, create content from research, or draft articles. Guides through research, brainstorming, outlining, and iterative drafting with version control.

Why use Blog Draft on TypingMind?

Because you install it once and use it with any model. Blog Draft is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Blog Draft in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/luongnv89/claude-howto/tree/main/03-skills/blog-draft. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Blog Draft?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Blog Draft?

As many as you like. As long as a model supports skills, you can use Blog Draft with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Blog Draft AI skill free?

Yes. It is published on GitHub by luongnv89 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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