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/danium/lateral-thinking/random-stimulusnpx skills add danium/lateral-thinking --skill random-stimulusgit clone --depth 1 https://github.com/danium/lateral-thinkingWhat 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 | $0.00121 | $0.01992 |
| Opus 5 | $0.00060 | $0.00996 |
| Sonnet 5 | $0.00024 | $0.00398 |
| Haiku 4.5 | $0.00012 | $0.00199 |
Grade A, and why
random-stimulus 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 — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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:
hourglassandcircadian rhythmboth 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.
What ships with it
2 files 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 · 98 lines · 121 tokens per session scan A a1ac73bd239b
random-stimulus is a skill published in the GitHub repository danium/lateral-thinking (286 stars, last pushed 1mo ago), licensed MIT. It adds 121 tokens to every session and 1,992 once invoked, about $0.0006 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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