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 skills add yogsoth-ai/stress-test --skill thought-experimentgit clone --depth 1 https://github.com/yogsoth-ai/stress-testWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/yogsoth-ai/stress-test/thought-experiment)<a href="https://agentmods.dev/skills/yogsoth-ai/stress-test/thought-experiment"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/stress-test/thought-experiment/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/yogsoth-ai/stress-test/thought-experiment"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/stress-test/thought-experiment.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What 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 5.1 | $0.00028 | $0.00825 |
| Opus 5 | $0.00014 | $0.00413 |
| Sonnet 5 | $0.00006 | $0.00165 |
| Haiku 4.5 | $0.00003 | $0.00082 |
Grade A, and why
thought-experiment 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 7d 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 — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Thought Experiment Strategy
Williamson methodology: construct precise, well-specified counterfactual scenarios that isolate individual variables.
Method
- causal-claim-extraction identifies the conclusion and its dependencies
- factor-enumeration identifies contingent vs. essential features
- counterfactual-scenario-construction builds precise thought experiments
- flip-point-detection identifies which scenario variations flip the conclusion
- necessity-evaluation determines if flipped factors are genuinely necessary
- load-bearing-identification distinguishes essential from contingent support
Design Principles
- Scenarios must be internally consistent (no impossible worlds)
- Changes must be minimal and precisely specified
- Background conditions must be held fixed except the target variable
- Conclusions must follow from the scenario, not from intuition pumps
Budget Table
| Parameter | S | M | L |
|---|---|---|---|
| Thought experiments | 3 | 8 | 15 |
| Variables isolated | 3 | 6 | 12 |
| Scenario precision checks | 1 | 3 | 6 |
Orchestration
causal-claim-extraction → factor-enumeration
→ [for each contingent feature]:
counterfactual-scenario-construction (precise scenario)
→ flip-point-detection (does conclusion hold?)
→ necessity-evaluation (is this genuinely necessary?)
→ load-bearing-identification (essential vs contingent)
Subagents
- causal-claim-extraction (dependency identification)
- factor-enumeration (contingent feature detection)
- counterfactual-scenario-construction (scenario design)
- flip-point-detection (conclusion testing)
- necessity-evaluation (necessity judgment)
- load-bearing-identification (classification)
Available Tactics
Optional, no fixed order; the final leaf is always a sop.
| Tactic | When to use |
|---|---|
| causal-necessity-testing | Tactic: Extract causal claims, evaluate probability of necessity (PN) and sufficiency (PS) for each, classify into necessity-sufficiency quadrants. |
| minimal-change-search | Tactic: Generate candidate changes, detect flip-points where conclusion reverses, measure fragility as distance to nearest flip. |
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.
- 7d ago First seen · 96 lines · 28 tokens per session scan A 0a959154c92f
thought-experiment is a skill published in the GitHub repository yogsoth-ai/stress-test (2 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 28 tokens to every session and 825 once invoked, about $0.0001 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 2026-09-03.
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