Thought Experiment

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

• 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.