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 minimal-change-searchgit 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/minimal-change-search)<a href="https://agentmods.dev/skills/yogsoth-ai/stress-test/minimal-change-search"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/stress-test/minimal-change-search/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/minimal-change-search"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/stress-test/minimal-change-search.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 | $0.00029 | $0.00588 |
| Opus 5 | $0.00015 | $0.00294 |
| Sonnet 5 | $0.00006 | $0.00118 |
| Haiku 4.5 | $0.00003 | $0.00059 |
Grade A, and why
minimal-change-search 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 — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Minimal Change Search Tactic
Find the smallest perturbation that flips the conclusion — closer flip-points mean higher fragility.
Orchestration
- causal-claim-extraction identifies the conclusion to test
- factor-enumeration generates candidate change dimensions
- counterfactual-scenario-construction builds scenarios with graduated changes
- flip-point-detection binary-searches for the minimal change that flips
- fragility-measurement computes distance from actuality to flip-point
- Repeat for each dimension within budget
- Report: nearest flip-point, fragility index, most vulnerable dimension
Search Strategy
- Start with large changes (clearly flips or clearly holds)
- Binary search between hold/flip boundary
- Record the minimal change magnitude per dimension
- Fragility = 1 / (distance to nearest flip-point)
Subagents Dispatched
- causal-claim-extraction (conclusion identification)
- factor-enumeration (dimension generation)
- counterfactual-scenario-construction (graduated scenarios)
- flip-point-detection (binary search)
- fragility-measurement (distance computation)
Termination Conditions
- All dimensions searched within budget
- Flip-point found with distance < threshold (extremely fragile)
- No flip-point found after maximum search depth (robust)
Available SOPs
Optional, no fixed order; the final leaf is always a sop.
| SOP | When to use |
|---|---|
| causal-claim-extraction | Extract all causal claims (X causes Y, X leads to Y, X enables Y) from an artifact, producing a structured list of cause-effect pairs. |
| counterfactual-scenario-construction | Construct precise, internally consistent counterfactual scenarios where specified factors are altered, then reason about the resulting conclusion. |
| factor-enumeration | List all key factors, conditions, and assumptions that support or enable the artifact's conclusion. |
| flip-point-detection | Find the minimal change magnitude along a dimension that causes the conclusion to flip from true to false. |
| fragility-measurement | Compute a fragility index from flip-point distances and degradation scores, summarizing how robust the conclusion is. |
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 · 69 lines · 29 tokens per session scan A 5a357ebdcea7
minimal-change-search is a skill published in the GitHub repository yogsoth-ai/stress-test (2 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 29 tokens to every session and 588 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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