thinking-thought-experiment
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.
How do I install this agent skill?
npx skills add https://github.com/tjboudreaux/cc-thinking-skills --skill thinking-thought-experimentIs this agent skill safe to install?
- Gen Agent Trust Hubpass
The skill provides a structured framework for counterfactual reasoning and mental simulations. It is purely instructional markdown with no executable code, network capabilities, or file access requirements. The configuration explicitly disables model tool invocation, ensuring a restricted and safe execution environment.
- Socketpass
No alerts
- Snykpass
Risk: LOW · No issues
What does this agent skill do?
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
- 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.
- 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.
- 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.
- 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.
- 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.
- 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 testisolated_variable: single change vs control worldinitial_conditions: frozen state and non-changesconsequence_chain: ordered mechanistic stepsinvariants: what still holdsbreak_points: first requirement failures and critical assumptionsimplication_bound: actions/checks justified by the chain onlydiscriminating_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.
How can the creator link this skill?
Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.
<a href="https://skillzs.dev/skills/tjboudreaux/cc-thinking-skills/thinking-thought-experiment">View thinking-thought-experiment on skillZs</a>