Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/nikeyes/stepwise-dev/hamburger-methodnpx skills add nikeyes/stepwise-dev --skill hamburger-methodgit clone --depth 1 https://github.com/nikeyes/stepwise-devWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00050 | $0.02513 |
| Opus 5 | $0.00025 | $0.01256 |
| Sonnet 5 | $0.00010 | $0.00503 |
| Haiku 4.5 | $0.00005 | $0.00251 |
Grade A, and why
hamburger-method scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 269 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Hamburger Method - Vertical Story Slicing
Expert in applying the Hamburger Method (by Gojko Adzic) to break down large features into small, safe, deliverable vertical slices.
When to Use This Skill
Use when:
- Feature feels large but not obviously splittable with story-splitting heuristics
- User asks "how to slice" or "how to deliver incrementally"
- Need to generate multiple implementation options
- Want to compose end-to-end vertical slices
Do NOT use when:
- Story has obvious "and", "or", "manage" indicators (use story-splitting instead)
- User is asking HOW to implement (use micro-steps-coach instead)
- Feature is already small (< 1 day work)
Core Process
When user describes a feature or story that needs slicing:
1. Identify Layers (Technical or Logical Steps)
Identify the main technical or business steps involved.
List 3-6 layers that form the complete flow.
Example for notification system:
- Layer 1: Detect triggering event
- Layer 2: Decide whom to notify
- Layer 3: Format the message
- Layer 4: Deliver the message
- Layer 5: Record delivery status
2. Generate 4-5 Options per Layer
This is MANDATORY: For EACH layer, generate at least 4-5 implementation options, from simplest to most complete.
Use a numbered system: 1.1, 1.2, 1.3... for Layer 1, then 2.1, 2.2, 2.3... for Layer 2, etc.
Quality gradient (low to high):
- Manual / hardcoded
- Semi-automated / configurable
- Fully automated / robust
- Scalable / multi-channel
- Enterprise-grade / resilient
Example for "Deliver the message" layer:
- 4.1: Manual email from your personal account
- 4.2: Scripted email via command line
- 4.3: Email via SMTP service (no retries)
- 4.4: Email via queuing system with retries
- 4.5: Multi-channel (email, push, SMS) with fallbacks
3. Force Radical Slicing
Always ask this question out loud in your response — do not skip it:
"If you had to ship something by tomorrow, what would you build?"
Then answer it explicitly by naming the specific options (by number) you would pick from each layer. This forces the absolute minimum viable slice, not just a "simple version".
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 269 lines · 50 tokens per session scan A fa63327872fd
hamburger-method is a skill published in the GitHub repository nikeyes/stepwise-dev (24 stars, last pushed 13d ago), licensed Apache-2.0. It adds 50 tokens to every session and 2,513 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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