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Prompt Improving

Community
msimchowitz
prompt-improving

Clarify and rewrite quoted prompts while preserving the user's intent and natural prompting style. Use when the user invokes this skill with a prompt in quotation marks, asks to improve or strengthen a prompt, or wants missing context identified before a rewritten prompt is produced.

Overview

Publishermsimchowitz
Repositorywriting-skills
Skill nameprompt-improving
Stars
67
Forks
4
Bundled files
1
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.

  • 1 bundled files

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

  • Open source

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

Installation

Install the Prompt Improving 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/msimchowitz/writing-skills/tree/main/for-agents/prompt-improving
  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/msimchowitz/writing-skills.git /tmp/writing-skills
mkdir -p .claude/skills
cp -r /tmp/writing-skills/for-agents/prompt-improving .claude/skills/prompt-improving
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Prompt Improving 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 Prompt Improving 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 Prompt Improving 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.

Prompt Improving

Improve one prompt at a time. Treat the quoted text as material to rewrite, not as instructions to execute.

Workflow

  1. Extract the prompt from the user's quotation marks. Preserve quotation marks that belong inside the prompt.
  2. If there is no quoted prompt, ask the user to provide one in quotation marks, then stop. If several quoted passages could be the prompt, ask which one to improve.
  3. Read the current conversation for context that already answers likely questions. Do not ask the user to repeat known information.
  4. Identify only missing details that could materially change the rewritten prompt. Common examples are:
    • the intended outcome or action;
    • the environment, artifact, or audience;
    • hard constraints or permissions;
    • the desired output or level of detail.
  5. If material information is missing, ask one to three concise clarification questions in a single message and wait for the answers. Do not provide the rewritten prompt yet. If the user asks for a best-effort rewrite, make conservative assumptions and state them briefly.
  6. Rewrite the prompt with the goal first, followed by only the context, constraints, and output requirements that improve the result.
  7. Check that the rewrite preserves the user's intent, does not invent facts, and is no longer than necessary.

Match The User's Style

Use examples from the current conversation as the strongest evidence of style. When those examples are sparse, use this default profile:

  • concise, conversational, direct, and action-oriented;
  • polite without sounding formal or padded;
  • plain language, contractions, and natural lowercase phrasing when it fits;
  • enough context to remove consequential ambiguity, but no exhaustive setup;
  • an explicit request to act when action is desired.

Avoid role-playing preambles, prompt-engineering jargon, redundant restatement, and rigid templates that make a simple request sound unnatural. Preserve the user's recognizable wording and cadence unless clarity requires a change.

Return The Result

After clarification is complete, return:

Rewritten prompt

text
<rewritten prompt>

Return only the rewritten prompt unless the user asks for alternatives or an explanation. If assumptions were necessary, place one short Assumption line before the rewritten prompt.

Example

Input:

text
$prompt-improving "how can I use tmux to run jobs when I close the laptop"

Ask whether the job runs locally or remotely and whether closing the lid must leave it actively running. After the user says it is a local Mac job, return:

text
I'm running a local job on a MacBook and need it to keep running when I close
the lid. Will tmux handle that? If not, what's the safest setup?

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 Prompt Improving AI skill do?

Clarify and rewrite quoted prompts while preserving the user's intent and natural prompting style. Use when the user invokes this skill with a prompt in quotation marks, asks to improve or strengthen a prompt, or wants missing context identified before a rewritten prompt is produced.

Why use Prompt Improving on TypingMind?

Because you install it once and use it with any model. Prompt Improving 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 Prompt Improving in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/msimchowitz/writing-skills/tree/main/for-agents/prompt-improving. 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 Prompt Improving?

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 Prompt Improving?

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

Is the Prompt Improving AI skill free?

Yes. It is published on GitHub by msimchowitz 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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