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Abstraction Power

Community
syahiidkamil
abstraction-power

Activate ATLAS pattern recognition mode. Identify repeated patterns, extract essential characteristics, and create reusable abstractions from concrete examples.

Overview

Publishersyahiidkamil
RepositorySoftware-Engineer-AI-Agent-Atlas
Skill nameabstraction-power
Stars
403
Forks
60
Bundled files
Instructions only
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 syahiidkamil on GitHub. Read the source before you install it.

Installation

Install the Abstraction Power 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/syahiidkamil/Software-Engineer-AI-Agent-Atlas/tree/main/.claude/skills/abstraction-power
  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/syahiidkamil/Software-Engineer-AI-Agent-Atlas.git /tmp/Software-Engineer-AI-Agent-Atlas
mkdir -p .claude/skills
cp -r /tmp/Software-Engineer-AI-Agent-Atlas/.claude/skills/abstraction-power .claude/skills/abstraction-power
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Abstraction Power 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 Abstraction Power 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 Abstraction Power 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.

Activate ATLAS abstraction thinking mode.

What is Abstraction?

Abstraction is the process of identifying essential features while hiding unnecessary details. It involves moving from specific, concrete examples to general, conceptual models.

The Abstraction Process

  1. Identify multiple concrete examples
  2. Analyze common patterns and features
  3. Remove specific details
  4. Extract essential characteristics
  5. Create a generalized model

Abstraction Example

Concrete instances:

  • sendEmail(to, subject, body) → connects to SMTP, formats message, delivers
  • sendSMS(phone, message) → connects to Twilio API, formats payload, delivers
  • sendPush(deviceId, title, body) → connects to FCM, formats notification, delivers

Pattern recognized: All three connect to a service, format a message, and deliver it.

Abstraction:

NotificationChannel {
  connect()
  format(content) → payload
  deliver(payload)
}

Three specific implementations collapsed into one interface. New channels (Slack, WhatsApp) plug in without changing the system.

Generalization Example

Concrete observations:

  • "Every time we add a new payment method, we modify the checkout function"
  • "Every time we add a new report type, we modify the export function"
  • "Every time we add a new auth provider, we modify the login function"

Generalized insight: The system violates the Open/Closed Principle. Adding a new variant forces modification of existing code.

Generalized solution: Use a registry/strategy pattern. New variants register themselves; the core function iterates over registered strategies without knowing their specifics.

The generalization isn't about one specific fix. It's recognizing the shape of the problem so you see it everywhere it appears.

When Invoked

Apply this abstraction lens to the current context:

  1. If analyzing code: Look for repeated patterns, similar structures, or duplicated logic that can be abstracted into reusable components
  2. If designing systems: Identify common behaviors and create generalized models
  3. If solving problems: Find the underlying pattern across specific examples

Visualization

Prefer flowcharts over sequence diagrams when visualizing abstractions. Flowcharts show the structure and relationships between abstracted components. Sequence diagrams show temporal interactions, which is useful but secondary to understanding the shape of the abstraction.

Use Mermaid diagrams. Default to graph TD (top-down flow) or graph LR (left-right flow). Only use sequenceDiagram when the insight is specifically about message ordering between actors.

Output Format

When applying abstraction power, provide:

Input (Concrete Examples)

List the specific instances being analyzed

Abstraction Process

  • Common features identified
  • Differences to ignore
  • Essential characteristics extracted

Output (Abstract Model)

The generalized model, class, pattern, or solution — with a Mermaid flowchart when the relationships benefit from visualization.

Key Benefits to Communicate

  • Reusability: Abstract models can be applied to many specific cases
  • Simplification: Complex systems become easier to understand
  • Maintenance: Changes to the abstract model propagate to all implementations
  • Scalability: New concrete instances can be created from the abstract template

Frequently asked questions

What does the Abstraction Power AI skill do?

Activate ATLAS pattern recognition mode. Identify repeated patterns, extract essential characteristics, and create reusable abstractions from concrete examples.

Why use Abstraction Power on TypingMind?

Because you install it once and use it with any model. Abstraction Power 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 Abstraction Power in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/syahiidkamil/Software-Engineer-AI-Agent-Atlas/tree/main/.claude/skills/abstraction-power. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Abstraction Power?

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 Abstraction Power?

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

Is the Abstraction Power AI skill free?

It is published on GitHub by syahiidkamil. Check the repository for licensing terms. 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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