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Provocation

Community
danium
provocation

Edward de Bono's Provocation (Po) technique — state something deliberately wrong or absurd about the problem, then extract useful "movement" from it instead of judging it. Use when a constraint feels unbreakable, when every design converges on the same shape, or to escape "the way it's always done". Triggers include "provocation", "po", "absurd statement", "deliberately break the rule", "the constraint feels unbreakable", "sacred cow". Do NOT use for analytical work like debugging, code review, or implementation tasks.

Overview

Publisherdanium
Repositorylateral-thinking
Skill nameprovocation
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 Provocation 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/provocation
  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/provocation .claude/skills/provocation
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Provocation 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 Provocation 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 Provocation 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.

Provocation (Po)

What this technique does

State something deliberately wrong, impossible, or absurd about the problem — then refuse to judge it. Instead, ask what useful movement the statement creates: the principle hiding inside it, what would happen moment-to-moment if it were true, what that makes different from today. The absurd statement is not a proposal; it is a stepping stone you stand on only long enough to reach somewhere you could not have walked to directly. It works because judgment and movement are opposite mental motions, and every honest constraint you carry is also a wall you have stopped seeing.

Source: Edward de Bono, Po: Beyond Yes and No (1972) and Serious Creativity (1992).

Workflow

Step 1: Confirm the target

A valid target is a concrete creative problem where the usual answers have gone stale: a design that keeps converging on the same shape, a constraint everyone treats as physics, a process nobody questions anymore. Good phrasings: "reinvent how we onboard new users", "our pricing page always ends up looking identical to competitors", "the approval step feels untouchable — challenge it". If the target is unclear, ask one focused question — "What's the problem, and which constraint or convention feels most fixed?"

Refuse requests to perform analytical work — debugging, reviewing code, implementing a change — and suggest an analytical approach instead. Redesigning or ideating about such a process is a valid creative target: "reinvent our code-review ritual" is in scope; "review this PR" is not.

Step 2: Surface the rules

List 4–6 operating rules or constraints that everyone treats as fixed about the target. Write them as flat declaratives, not questions — the things so obvious nobody says them out loud. These are the walls. Each one is a candidate to break, invert, or exaggerate in the next step. If you cannot name at least four, the target is probably too vague; go back to Step 1.

Step 3: Generate 4–6 provocations

Draw across the five classical operations. Prefix each with Po: and keep it to one line. A good Po is one you could not defend as a real suggestion — if it sounds reasonable, it is not a provocation yet, push it further.

  • Escape — drop a rule entirely. Take a rule from Step 2 and state its absence as fact. Po: the checkout has no prices.
  • Reversal — invert a relationship. Flip who does what to whom, or which direction something flows. Po: the user reviews the software's work.
  • Exaggeration — push a quantity to an impossible extreme (up or down to zero). Po: onboarding takes three seconds.
  • Distortion — scramble the normal sequence or swap the roles in it. Po: you pay the invoice before the work is scoped.
  • Wishful thinking — state a fantasy as accomplished fact. Po: the page reads the visitor's mind.

Cover at least three of the five operations across the batch. Do not run more than eight in one batch.

Step 4: Movement, per provocation

Never evaluate the provocation itself — do not ask whether it is good, safe, or possible. That is judgment, the wrong motion. Instead extract movement three ways:

  • (a) The principle — what general idea is hiding inside the absurd statement?
  • (b) Moment-to-moment — if it were literally true, what would happen, step by step, in the first minute?
  • (c) The difference — what is concretely different from how things work today?

Then shape any live thread into a real idea. Not every provocation reaches one — that is expected and honest (see Honesty mechanics). Show the movement work, not just the idea it produced.

Step 5: Meta-pattern scan

Scan across the ideas that landed for a structural property that kept recurring — "every provocation that paid off removed a step rather than adding one", "the strong ones all shifted work from the user onto the system", "three of them turned a cost into a signal". State the structural insight explicitly. This cross-provocation observation is often where the deepest result lives, and it also explains why the abandoned ones failed.

Step 6: Honest ranking

Pick the 2–4 sharpest directions and rank them. Say which feel weak, and why. Then offer next moves and stop: run more provocations, go deeper on one direction, switch to a different technique, or stop here. Never push the user to commit — divergence is your job; the decision is theirs.

Honesty mechanics

A provocation that yields no movement after two honest attempts is abandoned visibly. Show it, for example:

Po: customers pay us to leave — no movement found. Moving on.

Roughly 1 in 3 provocations will not pay off. A batch where every single Po produces a clean idea is a tell that the movement was faked — the operator judged the provocations into safe suggestions instead of moving off them. Show the failures; they are what proves the rest are real.

When the batch itself fails. If almost nothing moves, the problem is upstream of the provocations. Do not write more of them. Name the diagnosis, suggest the technique that fits it as the user's next move, and stop there — do not run it yourself:

  • Step 2 could not produce four rules everyone treats as fixed → the target is too vague, or it is not actually fenced. Suggest random-stimulus, which needs no constraint to push against.
  • The rules are real but every Po lands back on the same idea → you may be solving the wrong problem. Suggest concept-fan, which climbs to the concept the target serves.

What NOT to do

  • Don't defend or attack the provocation. It is not a proposal. Arguing "that would never work" or "actually that's reasonable" both miss the point — extract movement instead.
  • Don't generate polite, plausible provocations. If a Po could pass as a genuine suggestion, it is not a provocation. Push it until it is clearly absurd.
  • Don't skip the movement structure. Jumping straight from the Po to a finished idea hides the reasoning and usually smuggles in an idea you already had.
  • Don't run more than 8 provocations per batch. Quality drops and the movement work gets rushed.

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 Provocation AI skill do?

Edward de Bono's Provocation (Po) technique — state something deliberately wrong or absurd about the problem, then extract useful "movement" from it instead of judging it. Use when a constraint feels unbreakable, when every design converges on the same shape, or to escape "the way it's always done". Triggers include "provocation", "po", "absurd statement", "deliberately break the rule", "the constraint feels unbreakable", "sacred cow". Do NOT use for analytical work like debugging, code review, or implementation tasks.

Why use Provocation on TypingMind?

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

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

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 Provocation?

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

Is the Provocation 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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