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Article Prompts To Skills

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MengTo
article-prompts-to-skills

Convert an article, tutorial, or prompt pack into focused reusable AgentSkills, one independent capability per skill, with portable instructions, example prompts, working demos, preview screenshots, validation, gallery updates, and a narrow commit. Use when the user asks to turn an article's prompts, tutorial sections, design patterns, interactions, or workflow ideas into complete skills rather than leaving them as prose.

Overview

PublisherMengTo
RepositorySkills
Skill namearticle-prompts-to-skills
Stars
6.1K
Forks
717
Bundled files
7
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.

  • 7 bundled files

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

  • Open source

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

Installation

Install the Article Prompts To Skills 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/MengTo/Skills.git /tmp/Skills
mkdir -p .claude/skills
cp -r /tmp/Skills/agent-skills/codex/article-prompts-to-skills .claude/skills/article-prompts-to-skills
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Article Prompts To Skills 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 Article Prompts To Skills 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 Article Prompts To Skills 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.

Article Prompts to Skills

Turn source prompts into small, demonstrable capability packages. Preserve the useful behavior, not the source page's brand or layout.

1. Inspect Before Extracting

  1. Read the repository instructions and the complete source article.
  2. Run git status --short; preserve unrelated work.
  3. Inventory every explicit prompt, heading, example, asset, and acceptance criterion.
  4. Search existing SKILL.md files for overlapping capabilities before creating folders.
  5. If the source is raw HTML and the prompts do not exist yet, use $html-to-interaction-prompts first, then return here.

Do not infer a family of skills from a title alone. Trace each proposed skill to source evidence.

2. Build an Extraction Ledger

Create a working table before editing files:

Source promptReusable capabilityKeepRemoveSkill nameDemo proof

Apply these boundaries:

  • Create one skill per independently reusable behavior.
  • Merge steps only when separating them would make either step unusable.
  • Update an existing skill when its contract already covers the capability.
  • Skip decorative or editorial fragments that do not create a repeatable method.
  • Name skills after the outcome or mechanism, never after the source article.

3. Extract the Portable Contract

Keep the source's successful mechanics:

  • behavior and state transitions;
  • data model and parameter defaults;
  • timing, easing, spacing, and responsive rules;
  • accessibility, reduced-motion, and keyboard behavior;
  • performance constraints and failure modes;
  • acceptance checks that prove the result.

Remove source-specific packaging:

  • brand names, marketing copy, and proprietary content;
  • page layout that is unrelated to the capability;
  • hard-coded palettes, assets, and selectors;
  • incidental implementation choices that do not affect the outcome.

The result must transfer to a different subject, layout, and visual system without rewriting the core instructions.

4. Package Every Skill

Initialize every new folder with the installed skill-creator initializer, then complete this contract:

text
agent-skills/<category>/<skill-name>/
  SKILL.md
  agents/openai.yaml
  references/          # only when detailed reusable guidance is needed
  assets/ or scripts/  # only when the workflow genuinely reuses them
  demo/
    index.html
    PROMPT.md
    preview.jpg
    input.md            # required for workflow skills
    expected-output.md  # required for workflow skills

Write SKILL.md in imperative form. Keep only name and description in frontmatter. Put all trigger phrases in the description. Keep operational steps, constraints, pitfalls, and validation commands in the body.

Write agents/openai.yaml from the final skill:

  • use a human-readable display name;
  • keep the short description between 25 and 64 characters;
  • make the default prompt explicitly invoke $skill-name.

5. Write Three Useful Example Prompts

Put these headings in demo/PROMPT.md:

Minimal prompt

Invoke the skill and ask for one clear outcome.

text
Use $skill-name to add <capability> to <target>.

Recreate the demo

Describe the reference experience, implementation contract, deliverables, and acceptance checks. Specify what must remain local and self-contained.

Remix prompt

Change the subject, content, palette, and composition while preserving the mechanism, accessibility behavior, responsive rules, and performance contract.

Read references/example-packages.md for visual, mixed-source, and workflow examples.

6. Build Proof, Not Decoration

Make every demo original, self-contained, and inspectable:

  • demonstrate the core mechanism on the first screen;
  • use realistic content instead of labels such as “demo card”;
  • add controls only when they expose meaningful states;
  • support 390px through 1440px layouts;
  • use semantic HTML and visible focus states;
  • provide reduced-motion behavior for animated work;
  • keep dependencies local and avoid a build step unless the skill requires one;
  • use input.md and expected-output.md for nonvisual workflows.

Never treat a screenshot as the implementation. The HTML demo must work.

7. Validate the Complete Package

Run validation in proportion to the artifact:

  1. Run the skill creator's quick_validate.py on every new or changed skill.
  2. Run repository demo validation and any targeted syntax checks.
  3. Open each demo in the permitted browser at desktop and mobile sizes.
  4. Exercise the primary interaction, keyboard focus, and reduced-motion path.
  5. Confirm the console is clean.
  6. Capture a real browser preview at the repository's shared dimensions.
  7. Rebuild the demo and screenshot galleries, then validate again.
  8. Scan changed files for secrets, tokens, private paths, and private client data.

Do not claim visual or interaction verification from static file inspection alone.

8. Commit Only the Task

Stage the new skill folders and the gallery files they require. Review git diff --cached --stat and git diff --cached before committing. Leave pre-existing dirty files untouched.

Report:

  • the source-to-skill mapping;
  • the example prompt and demo paths;
  • validation and browser evidence;
  • the commit hash;
  • unrelated dirty files that remain outside the commit.

Failure Modes

  • Page clone: copying the source layout instead of extracting the mechanism.
  • Mega-skill: combining independent prompts into one vague skill.
  • Micro-fragments: turning every sentence into a skill without reusable behavior.
  • Theme lock-in: hard-coding the source's palette, assets, or copy.
  • Prompt-only package: omitting a functioning demo and preview.
  • Fake proof: claiming interaction verification without exercising it.
  • Dirty-tree spillover: staging unrelated modifications or generated files.

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 Article Prompts To Skills AI skill do?

Convert an article, tutorial, or prompt pack into focused reusable AgentSkills, one independent capability per skill, with portable instructions, example prompts, working demos, preview screenshots, validation, gallery updates, and a narrow commit. Use when the user asks to turn an article's prompts, tutorial sections, design patterns, interactions, or workflow ideas into complete skills rather than leaving them as prose.

Why use Article Prompts To Skills on TypingMind?

Because you install it once and use it with any model. Article Prompts To Skills 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 Article Prompts To Skills in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/MengTo/Skills/tree/main/agent-skills/codex/article-prompts-to-skills. 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 Article Prompts To Skills?

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 Article Prompts To Skills?

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

Is the Article Prompts To Skills AI skill free?

Yes. It is published on GitHub by MengTo 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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