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/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

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Install
$ npx -y skills add jabrena/plinth --skill 052-design-hamburger-method --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/052-design-hamburger-method

Context preview

The summary Claude sees to decide when to auto-load this skill.

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

SKILL.md

052-design-hamburger-method.SKILL.md
name: 052-design-hamburger-method
description: 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
license: Apache-2.0
metadata:
  author: Juan Antonio Breña Moral
  version: 0.18.0

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

1. **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.

2. **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.

3. **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.

4. **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.

5. **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.

6. **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](references/052-design-hamburger-method.md).

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