Agent skill

Random Stimulus

by danium in danium/lateral-thinking

Edward de Bono's Random Stimulus technique — force-fit a random unrelated object, place, or phenomenon onto a creative target to break familiar association patterns.

MITAuto-check passedDevelopment

Install Random Stimulus

skills CLI
$ npx skills add danium/lateral-thinking --skill random-stimulus -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install danium/lateral-thinking random-stimulus --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/danium/lateral-thinking.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/random-stimulus .claude/skills/random-stimulus && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
random-stimulus
GitHub stars
318
Token cost
~2.3k tokens
SKILL.md length
1,339 words
Files
3 (incl. references)
Skills in repo
10
Repo updated
First seen
Licence
MIT

At a glance

Edward de Bono's Random Stimulus technique — force-fit a random unrelated object, place, or phenomenon onto a creative target to break familiar association patterns.

  • Works in 6 steps: Confirm the target → Pull stimuli → For each stimulus, generate and show the… → …
  • Product ideation
  • SKILL.md covers What this technique does, Workflow, Honesty mechanics and What NOT to do, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Random Stimulus is an agent skill from danium/lateral-thinking. Edward de Bono's Random Stimulus technique — force-fit a random unrelated object, place, or phenomenon onto a creative target to break familiar association patterns. Use for product ideation, feature naming, brand direction, copywriting, architecture and design choices when ideas from outside the problem space would help. Triggers include "random stimulus", "random word", "force-fit", "de Bono", "inject a random object", "stare out the window", "see the tree and squeeze an idea". Do NOT use for analytical work…

Its SKILL.md is about 2.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including reference files (for example `references/stimulus-pools.md` and `references/worked-example.md`).

It sits in Development, covering Brainstorming and Copywriting. The repository describes itself as: Lateral thinking skills for AI agents - 8 techniques + a router. de Bono for your coding agent. The licence is MIT.

When your agent uses it

  • Product ideation
  • Brand direction
  • Architecture and design choices when ideas from outside the problem space would help
  • Include random stimulus

Example prompts

  • “random stimulus”
  • “random word”
  • “force-fit”
  • “/random-stimulus”

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Confirm the target
  2. Pull stimuli
  3. For each stimulus, generate and show the chain
  4. Embrace abandonment
  5. Find the meta-pattern
  6. Honest ranking, no closure pressure

What it can do on your machine

Read from SKILL.md and the folder at commit bde713d. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Random Stimulus loads about 2.3k tokens when it runs, and up to ~7.3k if it reads all its reference files. Until then it costs about 146 tokens; SKILL.md has 1,339 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~146
When it runs · the whole SKILL.md, loaded when a task matches
~2.3k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~7.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from danium/lateral-thinking at commit bde713d, republished under its MIT licence (© danium). 1,339 words, ~2,268 tokens.

Download SKILL.mdSave it as .claude/skills/random-stimulus/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
random-stimulus
description
Edward de Bono's Random Stimulus technique — force-fit a random unrelated object, place, or phenomenon onto a creative target to break familiar association patterns. Use for product ideation, feature naming, brand direction, copywriting, architecture and design choices when ideas from outside the problem space would help. Triggers include "random stimulus", "random word", "force-fit", "de Bono", "inject a random object", "stare out the window", "see the tree and squeeze an idea". Do NOT use for analytical work like debugging, code review, or implementation tasks.

Random Stimulus

What this technique does

Pick a random thing from outside the problem space — a tree, a glacier, a kettle. List its properties. Force a connection to the target. See what falls out.

The first stimuli you draw are usually trash. The third or fourth is where real ideas appear — which is why you draw a batch and not a single object. The technique works because staying inside the problem space routes you through familiar associations; an external stimulus breaks the routing and forces a fresh trajectory through the same target. The stimulus has a structural property — cyclical, layered, swarming, ephemeral, branching — that the target could have but doesn't yet. That mismatch is where new designs hide.

Source: Edward de Bono, Lateral Thinking: Creativity Step by Step (1970), specifically the Random Word / Random Object method.

Workflow

Step 1: Confirm the target

A valid target is a concrete creative problem: names for a feature, ideas for a product, a novel onboarding flow, how to position a brand. If the target is unclear, ask one focused question — "What's the creative problem, and are there hard constraints?" Default batch size is 8–12 stimuli.

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: Pull stimuli

Draw 8–12 stimuli from references/stimulus-pools.md. Three minimums, all checkable against the batch you drew — Step 3 requires you to label each stimulus with its pool, which is what lets a reader check them:

  • At least five distinct categories. Not "mixed" as a feeling — count them.
  • At least two concrete physical objects and at least one abstraction. Judge this per stimulus, not per pool: hourglass and circadian rhythm both live in Time & Cycles, but one is an object you could hold and the other is a rhythm you cannot. Mark each stimulus [concrete] or [abstract] beside its pool label so the count is visible. Pure-abstract batches feel intellectualized; pure-concrete batches feel mundane.
  • No two stimuli from the same category adjacent in the batch order.

If the user offers a triggering metaphor ("look out the window", "what's in my kitchen"), bias toward that pool but always include 2–3 unrelated stimuli to break the cluster. A fully on-theme batch defeats the purpose of randomness.

Track which stimuli have been used this session. On a second batch, draw fresh ones.

Step 3: For each stimulus, generate and show the chain

The chain is the artifact, not just the resulting idea. Show every link: the stimulus, its properties, the force-fit jump, the idea.

Open with a one-paragraph framing of why the technique works (first invocation only). Use a visual marker (emoji) per stimulus. Show the property list and the → force-fit arrow inline.

Label each stimulus with its pool and its kind — 🗼 The lighthouse beam — Vehicles & Transit [concrete]. The label is what makes Step 2's minimums checkable: a reader counts the distinct categories, spots two adjacent draws from the same pool, and tallies concrete against abstract. Unlabelled chains make the rule unfalsifiable, which is the same failure as "it feels strained."

Per-stimulus length varies by quality of result. A weak stimulus gets two sentences and abandonment. A strong one gets two to three paragraphs, developed into a concrete direction with precedent where it exists.

Step 4: Embrace abandonment

Roughly 1 in 4 stimuli will not pay off. Show this explicitly, for example: "🪡 The threading of a needle — every fit restated the target. Moving on."

Abandonment is a feature. It signals the method is genuine rather than retrofitted, and it reminds the user that quantity is what creates quality here. Forcing every stimulus to produce a good idea poisons the output.

The redundancy test. Before keeping a force-fit, ask: could I have reached this idea from the target alone, without the stimulus? If yes, the stimulus did no work — abandon it, however pretty the image. This is the test; "it feels strained" is not, because the operator who wants to look clever never feels strained.

The seductive failure is a stimulus that restates the target as a nicer picture of itself. A river delta laid over a churn dashboard yields "commits flow and deposit sediment" — vivid, and exactly what you already knew. Abandon it.

Hard rule: apply the redundancy test to every attempt, and abandon the stimulus the moment two successive attempts both fail it. A further attempt is worth making only to confirm the stimulus is dead, and it must be shown as such — "→ Third attempt: nothing new" — never as hope. Patience belongs to the batch, not to any one object.

Show full SKILL.md (557 more words)Show less
Step 5: Find the meta-pattern

After the batch, scan across the ideas that landed for a structural property that kept recurring — "all the strong hits had time or slowness as a feature", "three of the strongest cast the user as a defender, not a buyer", "most of these turned out to be community products, not tools".

Then scan the abandonments the same way. They usually share a reason, and that reason is itself a finding: if every dead stimulus died by restating the target, the target has an axis it is missing. Say what the abandonments had in common, not just that they happened. A good meta-pattern explains the failures as well as the hits.

This cross-stimulus observation is often where the deepest insight lives. State it explicitly. Name it mid-batch if it emerges before the end.

Step 6: Honest ranking, no closure pressure

Pick the 3–5 sharpest directions. Say which feel weak, and why. Do not push the user to commit.

End with an explicit offer: pull more stimuli, go deeper on one direction, switch technique, or stop. The user controls when the technique ends.

Honesty mechanics

Abandonment rule: two force-fit attempts, then the redundancy test from Step 4. A batch where every stimulus produces a viable idea is a tell that the output is fabricated — expect 2–3 abandonments per batch of 8–12.

When the batch itself fails. If more than half the stimuli die, do not draw more — that is the move that just failed. A target that nothing external will attach to is over-constrained or wrongly framed, and that is a diagnosis, not bad luck. Name the diagnosis, suggest the technique that fits it as the user's next move, and stop there. Do not run it yourself:

  • The target is phrased as a solution rather than a problem, or you suspect you are answering the wrong question → suggest concept-fan, which climbs to the concept the solution serves.
  • The target is fenced by a constraint so fixed that every stimulus bounces off it → suggest provocation, which breaks the constraint on purpose.

Meta-pattern step: never skip Step 5. The individual ideas matter less than the structural insight that emerges across them — and the abandonments are part of that scan, not excluded from it.

What NOT to do

  • Don't sanitize weird ideas. The unexpectedness is the value. If a force-fit produces something edgy or impractical, ship it as a direction; don't soften it.
  • Don't force every stimulus to produce a viable idea. Abandonment is honest output.
  • Don't keep a force-fit that restates the target. A vivid image is not a new idea. If you could have reached it without the stimulus, the stimulus did nothing — abandon it.
  • Don't answer a failed batch by drawing more stimuli. That is the move that already failed. Diagnose the target and suggest the technique that fits — as a next move for the user, not one you run yourself.
  • Don't repeat stimuli across batches in the same session.
  • Don't skip the meta-pattern step. It is where the gold is, and it covers the abandonments too.
  • Don't push the user toward a decision. The technique is divergent; convergence belongs to the user.
  • Don't run more than ~15 stimuli per batch. Returns diminish and quality suffers.

References

© danium, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files (references) in skills/random-stimulus of danium/lateral-thinking.

  • SKILL.md
  • references/stimulus-pools.md
  • references/worked-example.md

Open the folder on GitHubat commit bde713d

Compare with similar skills

Random Stimulus next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Random Stimulus compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Random Stimulus this skilldanium/lateral-thinking318—~2.3kAutomated safety check: PassMIT
Unslop TextJCarterJohnson/vibecoded-design-tells508—~3.5kAutomated safety check: PassCustom licence
Content Modelguardana/guardana152—~1.2kAutomated safety check: PassApache-2.0
Roam Evidence HardeningCranot/roam-code517—~1.5kAutomated safety check: PassApache-2.0
Technical Writingfrappe/skills146—~1.1kAutomated safety check: PassNone
Trellis Session Insightmindfold-ai/Trellis15k4 repos~1.7kAutomated safety check: PassAGPL-3.0

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Questions about Random Stimulus

What does Random Stimulus do?

Edward de Bono's Random Stimulus technique — force-fit a random unrelated object, place, or phenomenon onto a creative target to break familiar association patterns. Random Stimulus is an agent skill from danium/lateral-thinking. Edward de Bono's Random Stimulus technique — force-fit a random unrelated object, place, or phenomenon onto a creative target to break familiar association patterns.

When should I use Random Stimulus?

Random Stimulus fits situations like: product ideation; brand direction; architecture and design choices when ideas from outside the problem space would help; include random stimulus.

How do I install Random Stimulus in Claude Code?

Run `npx skills add danium/lateral-thinking --skill random-stimulus -a claude-code`. Or copy the skill folder (skills/random-stimulus in danium/lateral-thinking) into .claude/skills/random-stimulus in your project. Claude Code loads it when a task matches its description.

How do I install Random Stimulus in Codex?

Run `npx skills add danium/lateral-thinking --skill random-stimulus -a codex`. Or copy the skill folder (skills/random-stimulus in danium/lateral-thinking) into .agents/skills/random-stimulus in your project. Codex loads it when a task matches its description.

Can I use Random Stimulus in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add danium/lateral-thinking --skill random-stimulus -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/random-stimulus, .gemini/skills/random-stimulus, .github/skills/random-stimulus and .opencode/skills/random-stimulus in your project.

What does Random Stimulus need to run?

SKILL.md names no scripts, command-line tools or credentials: Random Stimulus is instructions for the agent only.

Does Random Stimulus access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Random Stimulus safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Random Stimulus use?

Random Stimulus is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Random Stimulus use?

About 2.3k tokens (SKILL.md is roughly 9.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 5.1k tokens, read only when the agent opens those files.

What are the alternatives to Random Stimulus?

Skills that share tags, products or a category with Random Stimulus: Unslop Text (JCarterJohnson/vibecoded-design-tells, 508 stars), Content Model (guardana/guardana, 152 stars), Roam Evidence Hardening (Cranot/roam-code, 517 stars) and Technical Writing (frappe/skills, 146 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Random Stimulus?

danium (a GitHub user) maintains it in danium/lateral-thinking, which has 318 GitHub stars. The repository holds 10 skills in this directory. The repository was last updated on September 13, 2026.

Source: danium/lateral-thinking on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.