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Scamper

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danium
scamper

SCAMPER (Bob Eberle) — run one existing idea, product, or process through seven systematic transformations - Substitute, Combine, Adapt, Modify/Magnify, Put to other use, Eliminate, Reverse/Rearrange. Use when there is already one working idea and the need is disciplined variations of it, e.g. "give me variations", "riff on this", "scamper", "what can we substitute or combine", "remix this feature". Do NOT use for analytical work like debugging, code review, or implementation tasks, and not for blank-page ideation (needs an existing idea as input).

Overview

Publisherdanium
Repositorylateral-thinking
Skill namescamper
Stars
325
Forks
24
Bundled files
2
LicenseMIT
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.

  • 2 bundled files

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

  • Open source

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

Installation

Install the Scamper 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/danium/lateral-thinking/tree/main/skills/scamper
  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/danium/lateral-thinking.git /tmp/lateral-thinking
mkdir -p .claude/skills
cp -r /tmp/lateral-thinking/skills/scamper .claude/skills/scamper
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Scamper 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 Scamper 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 Scamper 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.

SCAMPER

What this technique does

Take one existing thing — a feature, a product, a workflow — and push it through seven transformation lenses in fixed order. Each lens asks a different question: what could you swap out, what could you fuse it with, what could you borrow, what could you exaggerate or shrink, what else it could do, what could you cut, what could you flip. The value is coverage: the checklist forces you past the two or three variations you would have thought of unaided and into the ones you would have skipped. It is a divergent tool for an idea that already exists, not a way to invent one from nothing.

Source: Bob Eberle, SCAMPER: Games for Imagination Development (1971), building on Alex Osborn's checklist of idea-spurring questions.

Workflow

Step 1: Confirm the target

A valid target is an existing idea, artifact, or process: a shipped feature, a signup flow, a pricing model, a ritual your team runs. SCAMPER transforms something that already works; it cannot operate on a blank page. If the user brings no starting idea — "help me think of a product" — refuse and point them to a generative technique (a random-stimulus or free-association method) that manufactures ideas from nothing. This one needs raw material.

If the target is unclear, ask one focused question — "What's the existing idea, and what part of it is fixed versus open to change?" — then proceed.

Refuse requests to perform analytical work — "debug this", "review this code", "implement this change" — and suggest an analytical approach instead. But redesigning or reinventing such a process is a valid creative target: "reinvent our code-review ritual" is in scope; "review this PR" is not.

Step 2: Run all seven operations in order

Work the lenses in sequence — Substitute, Combine, Adapt, Modify/Magnify, Put to other use, Eliminate, Reverse/Rearrange. For each one, pull 3-4 pointed questions from references/question-bank.md and answer only the ones that actually bite against this target. Ignore the rest; the bank is a menu, not a form.

Zero hits on an operation is normal and expected. When a lens yields nothing real, mark it empty and move on — do not manufacture a variant to fill the slot.

Step 3: Collect the hits into concrete variants

Gather the questions that landed into named variants. Each variant states three things plainly: what changes, what it costs, and what it risks. A variant with no cost and no risk is usually a variant you have not thought through.

Step 4: Meta-pattern scan

Look back across the run: which operations kept producing hits, and which came up dry? Concentrated production is a signal. If Substitute and Eliminate both kept biting, the idea is probably carrying weight it does not need or resting on a swappable assumption — that is where it is soft. Name the pattern explicitly; it is often more useful than any single variant.

Step 5: Honest ranking with next-move offers

Rank the variants by real promise, say which ones are weak and why, and stop there. Offer next moves — go deeper on one variant, rerun a single operation harder, switch to a convergent technique to narrow, or stop — and let the user pick. Never push the user to commit.

Honesty mechanics

Operations with no bite are shown empty, not padded. Write the emptiness plainly, for example:

Eliminate: nothing left to remove — this idea is already minimal. Moving on.

A SCAMPER run where all seven operations "work" is a tell that the output is manufactured. On a real target, expect 3-5 of the seven to bite and the rest to come up empty. Showing the empty ones is what proves the run was genuine rather than retrofitted.

What NOT to do

  • Don't answer every question in the bank. Pick the ones with teeth against this specific target; skip the rest without comment.
  • Don't disguise the same variant under two operations. If "let users trigger it manually" shows up under both Substitute and Reverse, it is one idea, not two. Count it once.
  • Don't SCAMPER a vague target. Sharpen it first. Transforming a fuzzy idea produces seven fuzzy variants.
  • Don't pad empty operations. An honestly empty lens is a result, not a gap to fill.
  • Don't push the user toward a decision. The technique is divergent; convergence belongs to the user.

References

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 Scamper AI skill do?

SCAMPER (Bob Eberle) — run one existing idea, product, or process through seven systematic transformations - Substitute, Combine, Adapt, Modify/Magnify, Put to other use, Eliminate, Reverse/Rearrange. Use when there is already one working idea and the need is disciplined variations of it, e.g. "give me variations", "riff on this", "scamper", "what can we substitute or combine", "remix this feature". Do NOT use for analytical work like debugging, code review, or implementation tasks, and not for blank-page ideation (needs an existing idea as input).

Why use Scamper on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/danium/lateral-thinking/tree/main/skills/scamper. 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 Scamper?

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 Scamper?

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

Is the Scamper AI skill free?

Yes. It is published on GitHub by danium under the MIT 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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