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Computer Organization Visualization

Community
mingchen666
computer-organization-visualization

Use this skill whenever the user wants visual learning for computer organization, data representation, two's complement, floating point, cache mapping, memory hierarchy, instruction format, CPU datapath, control signals, pipeline timing, bus, I/O, DMA, interrupts, or 408 computer organization review.

Overview

Publishermingchen666
RepositoryReviva
Skill namecomputer-organization-visualization
Stars
293
Forks
31
Bundled files
4
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.

  • 4 bundled files

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

  • Open source

    Published by mingchen666 on GitHub. Read the source before you install it.

Installation

Install the Computer Organization Visualization 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/mingchen666/Reviva/tree/main/electron/builtin-assets/skills/computer-organization-visualization
  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/mingchen666/Reviva.git /tmp/Reviva
mkdir -p .claude/skills
cp -r /tmp/Reviva/electron/builtin-assets/skills/computer-organization-visualization .claude/skills/computer-organization-visualization
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Computer Organization Visualization 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 Computer Organization Visualization 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 Computer Organization Visualization 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.

Computer Organization Visualization Skill

Create precise visual explanations for computer organization. Emphasize bit fields, data movement, component roles, timing, and calculation steps.

Use For

  • two's complement range, overflow, fixed/floating-point representation;
  • IEEE-like floating format explanation when the user's material specifies the format;
  • Cache address split, direct/associative/set-associative mapping, replacement, AMAT;
  • main memory organization, interleaving, address lines, word/byte addressing;
  • instruction format, addressing modes, control signals;
  • single-cycle/multi-cycle CPU data path;
  • pipeline timing, stalls, forwarding, hazards, speedup;
  • interrupts, DMA, buses, I/O path.

Output Modes

TopicPreferred visual
Data representationbit field strip + conversion steps
Cacheaddress split + cache set/table + hit/miss timeline
CPU datapathcomponent diagram + highlighted data/control path
Pipelinecycle-by-instruction grid + hazard markers
Interrupt/DMAsequence diagram + bus ownership timeline

Bundled Template

Choose the closest bundled template:

  • assets/templates/architecture-stepper.html - CPU datapath, instruction execution, bus/I/O sequence, DMA/interrupt flow.
  • assets/templates/cache-mapping.html - Cache address split, mapping, tag comparison, hit/miss, replacement.
  • assets/templates/pipeline-grid.html - pipeline cycle table, hazards, stalls, forwarding, branch penalty.

Replace the DATA object with the target CPU/Cache/pipeline scenario. Keep the register/memory/formula panels and cycle table for exam-transfer value.

Follow the shared UI standard in /skills/cs-course-learning/references/visual-template-ui.md when available: learning-workbench layout, stable controls, state table, step inspector, and exam-transfer panel.

Research-Informed Design Patterns

Use patterns from educational architecture simulators such as Ripes, QtMips, ARM graphical micro-architecture simulators, and pipeline/cache teaching tools:

  • make registers, memory, instruction memory, data memory, and control signals visible;
  • highlight the active data path for the current instruction;
  • show cycle-by-cycle pipeline occupancy;
  • show stalls, forwarding, branch handling, and cache hit/miss as explicit events;
  • allow small user-provided instruction/address examples;
  • pair diagrams with formula substitution and exam-check tables.

Topic Coverage Checklist

For 408/期末复习, cover these families when relevant:

  • data representation: bases, complement, overflow, fixed/floating point, error checking;
  • memory hierarchy: locality, Cache mapping, replacement, write policy, AMAT;
  • instruction system: instruction format, addressing modes, ISA/ABI boundary;
  • CPU datapath: fetch/decode/execute/memory/writeback, control signals;
  • pipeline: hazards, stalls, forwarding, branch penalty, speedup;
  • I/O: interrupts, DMA, bus arbitration, memory-mapped I/O.

Required Structure

  • Show bit widths, units, and field boundaries explicitly.
  • Use arrows for data movement and dashed arrows for control signals.
  • Pair every formula with the specific numbers substituted into it.
  • Include an "exam check" list: unit, bit count, boundary, replacement rule, and final answer.
  • For CPU/pipeline pages, include a register table, memory table, pipeline table, and current-instruction panel when relevant.

Accuracy Rules

  • Do not infer word length, block size, associativity, replacement policy, or address width if the user has not provided them; ask or mark as assumption.
  • Distinguish bit, byte, word, word length, storage word, and instruction word.
  • For pipeline questions, separate ideal time, stalls, fill/drain, throughput, and speedup.
  • For Cache questions, state address width, block size, line/set count, associativity, replacement policy, and write policy before calculating.

Coordination

  • Use technical-diagram-skill for CPU data path, cache mapping diagrams, pipeline timing grids, and bus sequence diagrams.
  • Use learning-visualization-skill for interactive HTML explanations and step controls.
  • Use cs-course-learning for broader 408 planning and mistake diagnosis.

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 Computer Organization Visualization AI skill do?

Use this skill whenever the user wants visual learning for computer organization, data representation, two's complement, floating point, cache mapping, memory hierarchy, instruction format, CPU datapath, control signals, pipeline timing, bus, I/O, DMA, interrupts, or 408 computer organization review.

Why use Computer Organization Visualization on TypingMind?

Because you install it once and use it with any model. Computer Organization Visualization 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 Computer Organization Visualization in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/mingchen666/Reviva/tree/main/electron/builtin-assets/skills/computer-organization-visualization. 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 Computer Organization Visualization?

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 Computer Organization Visualization?

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

Is the Computer Organization Visualization AI skill free?

It is published on GitHub by mingchen666. 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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