052 Design Hamburger Method

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jabrena

052-design-hamburger-method

Use when a large feature, story, plan, or spec idea needs to be split into small vertical slices with the Hamburger Method. This should trigger for requests such as Split this oversized story; Find the smallest useful slice; Break this feature into vertical slices; Apply the Hamburger Method; Turn this broad plan into tracked slices. Part of Plinth Toolkit

Overview

Publisher	jabrena
Repository	`plinth`
Skill name	`052-design-hamburger-method`
Stars	455
Forks	95
Bundled files	1
License	Apache-2.0
Links	Skill source Repository Homepage

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 jabrena on GitHub. Read the source before you install it.

Installation

Install the 052 Design Hamburger Method AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/jabrena/plinth/tree/main/skills/052-design-hamburger-method
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.

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/jabrena/plinth.git /tmp/plinth
mkdir -p .claude/skills
cp -r /tmp/plinth/skills/052-design-hamburger-method .claude/skills/052-design-hamburger-method

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable 052 Design Hamburger Method 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 052 Design Hamburger Method 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 052 Design Hamburger Method 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.

Hamburger Method Design

Guide Java teams through the Hamburger Method for splitting oversized work into small, valuable, end-to-end vertical slices. This is an interactive SKILL.

What is covered in this Skill?

Recognizing oversized feature, story, plan, or spec work
Identifying 3-6 functional or workflow layers that participate in delivering value
Generating 4-5 implementation or quality options per layer
Challenging scope with the smallest useful version question
Filtering options that are too costly, redundant, irreversible, or unnecessary for early learning
Composing one first vertical slice and follow-up slices
Self-checking value, size, testability, deliverability, and issue-tracking suitability
Routing plan, OpenSpec, GitHub issue, and Jira follow-up through the existing planning skills

Constraints

Split oversized work into vertical slices that deliver observable value, not isolated horizontal technical tasks.

MUST read references/052-design-hamburger-method.md before applying the method
MUST identify 3-6 functional or workflow layers before selecting a slice
MUST generate 4-5 options per layer, ordered from simplest acceptable option to richer options
MUST challenge scope with the smallest-useful-version question before recommending a first slice
MUST filter costly, redundant, irreversible, or unnecessary options before composing the first slice
MUST keep recommended work as vertical slices that deliver observable value
MUST NOT present isolated technical layers as independently shippable stories

When to use this skill

Apply the Hamburger Method
Split this oversized story
Find the smallest useful slice
Break this feature into vertical slices
Turn this broad plan into tracked slices
This feature is too large

Workflow

Recognize Oversized Work

Read references/052-design-hamburger-method.md, then restate the large feature, story, plan, or spec idea and why ordinary implementation task decomposition would be too broad, risky, or horizontal.

Map Layers and Options

Identify 3-6 functional or workflow layers needed for observable value. For each layer, generate 4-5 implementation or quality options ordered from the simplest acceptable choice to richer choices.

Challenge Scope

Ask: "If this had to ship tomorrow, what would be the smallest useful version?" Use the answer to remove options that are too costly, redundant, irreversible, or unnecessary for early learning.

Compose the First Slice

Select one option from each relevant layer to create the smallest useful end-to-end vertical slice. Explain the user-visible value, validation signal, and why rejected layer options wait for later slices.

Plan Follow-Up Slices

Propose follow-up vertical slices that incrementally improve quality, automation, robustness, reach, observability, operational behavior, or supported workflows without turning them into isolated technical layers.

Self-Check and Route Follow-Up

Check every slice for value, size, testability, deliverability, and issue-tracking suitability. Route implementation planning through 041-planning-plan-mode, spec-level changes through 042-planning-openspec, GitHub issue work through 043-planning-github-issues, Jira work through 044-planning-jira, and Azure DevOps work through 045-planning-azure-devops.

Reference

For detailed guidance, examples, and constraints, see references/052-design-hamburger-method.md.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

references/052-design-hamburger-method.md10 KB

Frequently asked questions

What does the 052 Design Hamburger Method AI skill do?

Why use 052 Design Hamburger Method on TypingMind?

Because you install it once and use it with any model. 052 Design Hamburger Method 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 052 Design Hamburger Method in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/jabrena/plinth/tree/main/skills/052-design-hamburger-method. 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 052 Design Hamburger Method?

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 052 Design Hamburger Method?

As many as you like. As long as a model supports skills, you can use 052 Design Hamburger Method with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the 052 Design Hamburger Method AI skill free?

Yes. It is published on GitHub by jabrena under the Apache-2.0 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Hamburger Method Design

Constraints

When to use this skill

Workflow

Reference

Bundled files

Frequently asked questions

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