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Public Readme Polisher

Community
100yenadmin
public-readme-polisher

Use when improving a public README, repository homepage, docs landing page, or developer-facing first impression.

Overview

Publisher100yenadmin
Repositoryfable-token-saving-skills-orchestrator
Skill namepublic-readme-polisher
Stars
101
Forks
5
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by 100yenadmin on GitHub. Read the source before you install it.

Installation

Install the Public Readme Polisher 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/100yenadmin/fable-token-saving-skills-orchestrator/tree/main/skills/public-readme-polisher
  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/100yenadmin/fable-token-saving-skills-orchestrator.git /tmp/fable-token-saving-skills-orchestrator
mkdir -p .claude/skills
cp -r /tmp/fable-token-saving-skills-orchestrator/skills/public-readme-polisher .claude/skills/public-readme-polisher
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Public Readme Polisher 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 Public Readme Polisher 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 Public Readme Polisher 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.

Public README Polisher

Polish the README as the repo's public front door: credible, scannable, actionable, and claim-safe.

Use When

  • a README feels plain
  • a repo needs a public first impression
  • a docs landing page needs clearer value, install path, or proof
  • a visual asset could make the repo easier to understand

Process

  1. Audit repo truth: purpose, install path, tests, license, security, CI, docs, examples, and public claim boundaries.
  2. Define the public promise in one paragraph: who it helps, what it gives them, and what it does not guarantee.
  3. Improve the first viewport: title, optional hero, badges, concise opening, quick action, and a scannable "what you get" table.
  4. Add scanning structure: quick start, workflow diagram when useful, proof or sources near the claim, and links to deeper docs.
  5. Validate links, images, alt text, docs scan, tests, and the scorecard below.

Visual Asset Rules

  • Use one purposeful hero only when it clarifies the repo.
  • For generated images: no embedded text, no logos, no watermarks.
  • Inspect the image before committing; reject generated image with readable fake text, broken UI, mascot drift, or misleading claims.
  • Save README assets under assets/readme.
  • Add alt text that explains the image function.

Claim Safety

  • Cite official sources for factual pricing, cache, legal, API, or security claims.
  • Say "patterns that worked for us" for experience-based recommendations.
  • Avoid guaranteed savings, official endorsement, universal safety claims, or "works for every workflow" language.
  • Keep related tools optional unless the repo truly depends on them.

Scorecard

Score each category 0-2. Pass at 13/16 or higher.

Category2 means
First-viewport signalrepo purpose, visual tone, badges, and install path are clear without scrolling
Audience/value clarityreader knows who it is for and what problem it solves
Scannabilitytables, bullets, headings, and diagrams make scanning easy
Actionabilityquick start and next links are concrete and current
Trust/proofsources, CI, license, tests, and safety boundaries support the claims
Visual polishassets feel intentional, domain-fit, and not generic stock decoration
Accessibility/asset hygienealt text, local paths, file size, and image rendering are sane
Claim safetyclaims are bounded, sourced where needed, and public-safe

Automatic blockers: private paths, secrets, broken local links, missing install path, false or guaranteed claims, generated image with readable fake text, missing alt text, failing docs scan.

Common Mistakes

  • Making a marketing page that hides the actual install/use path.
  • Adding a pretty image that does not explain the repo.
  • Moving official citations away from the claims they support.
  • Replacing precise safety boundaries with vague hype.
  • Claiming completion without running the scorecard.

Frequently asked questions

What does the Public Readme Polisher AI skill do?

Use when improving a public README, repository homepage, docs landing page, or developer-facing first impression.

Why use Public Readme Polisher on TypingMind?

Because you install it once and use it with any model. Public Readme Polisher 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 Public Readme Polisher in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/100yenadmin/fable-token-saving-skills-orchestrator/tree/main/skills/public-readme-polisher. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Public Readme Polisher?

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 Public Readme Polisher?

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

Is the Public Readme Polisher AI skill free?

Yes. It is published on GitHub by 100yenadmin 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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