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Blog Post Structure Pass

Organization
microsoft
blog-post-structure-pass

Use this skill when the user asks to restructure, reorganise, improve, rewrite, tighten, or strengthen a blog post, article, newsletter, essay, or thought-leadership draft.

Overview

Publishermicrosoft
Repositorycat-agent-skills
Skill nameblog-post-structure-pass
Stars
95
Forks
115
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 microsoft on GitHub. Read the source before you install it.

Installation

Install the Blog Post Structure Pass 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.
    https://github.com/microsoft/cat-agent-skills/tree/main/submissions/blog-post-structure-pass
  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/microsoft/cat-agent-skills.git /tmp/cat-agent-skills
mkdir -p .claude/skills
cp -r /tmp/cat-agent-skills/submissions/blog-post-structure-pass .claude/skills/blog-post-structure-pass
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Blog Post Structure Pass 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 Post Structure Pass 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 Post Structure Pass 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.

Blog Post Structure Pass

Use this skill to improve the structure, argument, flow, and readability of a blog post while preserving the source facts and the author's intended point of view.

Core rules

  • Do not invent evidence, examples, client stories, dates, results, or quotes.
  • Preserve the author's stance unless asked to change it.
  • Improve the shape of the argument before polishing sentences.
  • Keep the revised post suitable for the intended audience and channel.
  • If important evidence is missing, mark it as a gap rather than filling it in.

Default post skeleton

Use this skeleton as a guide, not a rigid template:

  1. Hook / tension - Why this matters now.
  2. Problem - What people usually misunderstand or struggle with.
  3. Reframe - The more useful way to think about it.
  4. Practical implications - What changes in decisions, behaviour, governance, delivery, or operations.
  5. Example or proof - Evidence from supplied material.
  6. Takeaway - What the reader should do, question, or remember.

Workflow

  1. Read the source post or draft.
  2. Identify the current thesis and intended audience.
  3. Diagnose structural issues: weak opening, unclear argument, repetition, missing transitions, unsupported claims, premature solutioning, or weak ending.
  4. Create a revised outline.
  5. Rewrite the post into the improved structure.
  6. Preserve factual claims from the source and avoid adding unsupported material.
  7. Provide a short change note only if useful.

Output format

markdown
# [Revised title]

[Rewritten post]

---

## Change notes

- [Only include important changes, assumptions, or evidence gaps.]

If the user asks for the structure only, use:

markdown
## Recommended structure

1. [Section]
2. [Section]
3. [Section]

## Rationale

[Short explanation]

References

This skill includes supporting reference material. Read the relevant reference file when the task needs additional structure, rubric detail, examples, or checklist support.

  • references/post-structure-patterns.md - use this when additional structure, examples, or checks are useful for the task.

Quality checklist

Before responding, check:

  • The revised post has a clear thesis.
  • The opening creates relevance quickly.
  • The middle develops the argument rather than listing points.
  • The ending lands the insight or next action.
  • No unsupported facts have been added.
  • The copy sounds natural and human.

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 Post Structure Pass AI skill do?

Use this skill when the user asks to restructure, reorganise, improve, rewrite, tighten, or strengthen a blog post, article, newsletter, essay, or thought-leadership draft.

Why use Blog Post Structure Pass on TypingMind?

Because you install it once and use it with any model. Blog Post Structure Pass 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 Post Structure Pass in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/microsoft/cat-agent-skills/tree/main/submissions/blog-post-structure-pass. 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 Post Structure Pass?

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 Post Structure Pass?

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

Is the Blog Post Structure Pass AI skill free?

Yes. It is published on GitHub by microsoft 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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