/thinking-thought-experiment

name: thinking-thought-experiment
description: 'When a real test is too rare, large, or irreversible, run a controlled counterfactual: isolate one variable, fix conditions, trace the mechanistic chain, and bound what the result implies.'
disable-model-invocation: true

Thought Experiment

When empiricism is out of reach, run a disciplined counterfactual: one isolated change, fixed conditions, step-by-step mechanism, and a hard bound on implications.

When to Use

• You need behavior under failure, scale, or policy you cannot cheaply trigger or measure (region outage, 100x load, one-way architecture).
• A decision is expensive or irreversible and a mental trace can surface break points before commit.
• Edge cases are too costly to stage, but a mechanistic chain can still expose missing controls.

When NOT to Use

• A cheap real test exists (load test, flag, query, spike) → run the test; do not substitute imagination.
• Adversarial security attack-path work → use red-team structure, not free-form scenarios.
• You already know the mechanism and only need a decision under known facts → decide; do not dramatize.
• Vague "what if everything" brainstorming without a single isolated variable → tighten or stop.

Procedure

1. **State the question and isolation.** Name exactly one primary variable or counterfactual change. Freeze all other conditions as the control world. Reject multi-variable "and also" scenarios. 2. **Fix initial conditions.** Specify system state, load, configuration, actors, and what is *not* changed. Write values concrete enough that another agent could replay the setup. 3. **Trace the mechanism step by step.** From t0, record what fails, queues, retries, or adapts next—and why—using known components and policies only. No hand-wavy "then everything collapses"; each step needs a causal link. 4. **Extract invariants and break points.** Note what still holds (invariants) and the first step where the system violates a requirement (capacity, correctness, safety, UX). Mark assumptions that, if false, void the chain. 5. **Bound implications.** Map insights only to actions or checks justified by the chain (limits, guards, monitoring, redesign). Label speculative leaps beyond the isolation as out of bound. 6. **Name a discriminating real check, then stop.** For the weakest link, state the cheapest observation or experiment that would confirm or kill it. Stop after one controlled chain with bounded implications; if a link is cheaply testable now, exit to that test instead of further imagination.

Output

Emit a thought-experiment record:

• `question`: what behavior or decision is under test
• `isolated_variable`: single change vs control world
• `initial_conditions`: frozen state and non-changes
• `consequence_chain`: ordered mechanistic steps
• `invariants`: what still holds
• `break_points`: first requirement failures and critical assumptions
• `implication_bound`: actions/checks justified by the chain only
• `discriminating_check`: cheapest real observation to confirm or kill the weak link

Verification

• **Isolation check:** more than one free variable without a stated control → invalid; reset.
• **Mechanism check:** any step without a causal link to a known component/policy → rewrite or drop.
• **Implication bound:** recommendations not entailed by the chain are out of scope.
• **Empiricism override:** if a real test became available mid-analysis, stop the thought experiment and test.
• **Over-application guard:** do not use this skill for ordinary debugging you can reproduce, or as a substitute for red-team threat modeling.
• **Stop:** one isolated counterfactual → full chain → bounded implications + discriminating check; no scenario sprawl.