Kill The Wall Of Text logo

Kill The Wall Of Text

Organization
swan-gtm
kill-the-wall-of-text

Use this skill when work is about to go from one person to another: a report, a plan, an analysis, a memo, meeting notes, research, a code change, a proposal, or a raw AI answer. Produces an interactive, human-readable page that the recipient can review in seconds, with a ten-second top, a two-minute body, and folded evidence, written in Simplified Technical English and signed by the sender after a review loop. Trigger phrasings: "make this digestible", "make this readable", "de-slop this", "turn this into an artifact", "one-pager", "exec view", "I need to forward this", "nobody will read this", "show me what I must decide".

Overview

Publisherswan-gtm
Repositorygtm-skills
Skill namekill-the-wall-of-text
Stars
216
Forks
103
Bundled files
6
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.

  • 6 bundled files

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

  • Open source

    Published by swan-gtm on GitHub. Read the source before you install it.

Installation

Install the Kill The Wall Of Text 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/swan-gtm/gtm-skills/tree/main/skills/amos-bar-joseph/kill-the-wall-of-text
  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/swan-gtm/gtm-skills.git /tmp/gtm-skills
mkdir -p .claude/skills
cp -r /tmp/gtm-skills/skills/amos-bar-joseph/kill-the-wall-of-text .claude/skills/kill-the-wall-of-text
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Kill The Wall Of Text 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 Kill The Wall Of Text 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 Kill The Wall Of Text 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.

Applies each time raw work must go to a person who did not make it. Produces one interactive page that the recipient can review in seconds, and that the sender has read and signed.

The rule: work like a lawyer who talks to a five-year-old. The lawyer signs each word and stands behind it. Nobody gives a five-year-old ten pages of text; someone shows the story.

The measure: work is slop if the review takes longer than the generation. This play inverts that ratio. The build takes longer, so that the review takes seconds.

The three layers

Each page has all three.

  1. Top, 10 seconds. The verdict in one sentence. The ask: what the recipient must do, and by when. A maximum of three key numbers.
  2. Body, 2 minutes. An interactive view in the shape that fits the content.
  3. Evidence, on demand. Sources, method, assumptions, and the content that was cut. Folded. Nothing is lost, and nothing is in the way.

Test for the top: if the recipient reads only the top and closes the page, do they know the answer and their next action?

The play

  1. Read all of the raw work. Extract the recipient, the ask, the verdict, each fact with its location in the source, and the gaps: missing data, contradictions, claims with no evidence.
  2. Ask a maximum of two questions, in one message. "Who gets this, and what must they do with it?" and "What is the one thing they must understand?" Offer a proposed verdict, so that the human can say yes. Do not ask what the context answers. A skipped question becomes a labeled assumption, not a second question.
  3. Select the shape. A report becomes a dashboard. A plan becomes a one-page view. A decision becomes an option comparison. A code change becomes a diagram of what moved. Read references/shape-table.md for the ten shapes and the rule for two shapes that fit.
  4. Write each visible word in Simplified Technical English. Short active sentences, one word for one thing, no idioms, absolute dates, one named owner for each action. Read references/writing-rules.md before you write; it also has the fidelity rules and the cases where the two sets of rules meet.
  5. Publish the first version quickly. Start from references/page-skeleton.md. The first version shows a "Draft, not signed" banner. Chat gets one line: "This is V1. Tell me what goes on top, what to cut, and what is wrong."
  6. Check before each publish. Read references/pre-publish-check.md. It has a script that finds sentences that break the writing rules, calculates the read time, and lists each number that is not in the source.
  7. Run the review loop. The human decides what goes on top, what to cut, and what is wrong. Each block has Keep, Cut, Fix, and Move up controls, and one button copies the feedback as text for the chat. Apply the feedback to the current page; do not build it again. Read references/review-loop-and-signing.md.
  8. Get the signature. When the human approves, ask one time: "Did you read all of it, and do you stand behind it?" On yes, the banner changes to "Signed by NAME, DATE". No signature, no change.

references/worked-example.md shows one case from raw work to signed page, with the weak version adjacent to the good one.

What good looks like

  • The best operator starts from the recipient's next action, not from the document. The first question is "what must this person do after they read it?" The shape, the top, and the cuts all follow from that answer. The average operator starts from the structure of the source and keeps it.
  • The common mistake is text in boxes. The same paragraphs, cut into cards, with twelve numbers of equal size. It looks better and reads no faster. If the shape of the page is the shape of the source, the work did not occur.
  • The top states the answer, not the topic. "The quarter missed the plan by 12%, and small-business churn is the cause" is a top. "This report covers quarterly performance" is a label.
  • Read time is a number on the page. Top plus the longest tab, divided by 200 words for each minute. More than three minutes means more cuts or more folds.
  • Each number has a source. A number that is not in the source has a calculated or assumed tag, or it is wrong. A conflict between two sources shows the two values, on top if the number is on top.
  • The first version is about 80% correct, and that is the plan. The 20% that the human changes is what only the human knows: what this recipient will ask first. A good page makes that 20% fast to change. A page that the human signs with no changes is a warning that the human did not read it.
  • Interaction does work. A fold hides depth. A filter answers a question. A check box records an action. Animation and hover effects do none of these.
  • The chat stays short. One line after each publish. The page is the work surface.

Rules

  • MUST show the "Draft, not signed" banner until the human confirms that they read all of it.
  • MUST keep cut content in the evidence layer, where the human can restore it.
  • MUST tag each assumption, calculation, proposal, unverified claim, and conflict where it occurs.
  • MUST write "Not in the source" for a missing owner, date, or number.
  • MUST make the page work on a phone with no sideways scroll, and print with all tabs open.
  • NEVER invent a number, an owner, a date, or a quote.
  • NEVER write a signature that the human did not give.
  • NEVER make a claim stronger or weaker than the source makes it.
  • NEVER put more than three key numbers on top, or more than four tabs in the body.
  • NEVER deliver a long chat message or a text dump in place of the page.
  • NEVER say that a check was made when it was not made.

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 Kill The Wall Of Text AI skill do?

Use this skill when work is about to go from one person to another: a report, a plan, an analysis, a memo, meeting notes, research, a code change, a proposal, or a raw AI answer. Produces an interactive, human-readable page that the recipient can review in seconds, with a ten-second top, a two-minute body, and folded evidence, written in Simplified Technical English and signed by the sender after a review loop. Trigger phrasings: "make this digestible", "make this readable", "de-slop this", "turn this into an artifact", "one-pager", "exec view", "I need to forward this", "nobody will read t...

Why use Kill The Wall Of Text on TypingMind?

Because you install it once and use it with any model. Kill The Wall Of Text 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 Kill The Wall Of Text in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/swan-gtm/gtm-skills/tree/main/skills/amos-bar-joseph/kill-the-wall-of-text. 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 Kill The Wall Of Text?

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 Kill The Wall Of Text?

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

Is the Kill The Wall Of Text AI skill free?

Yes. It is published on GitHub by swan-gtm 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇