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 appleweiping/WEIPING_WIKI --skill aris-experiment-auditgit clone --depth 1 https://github.com/appleweiping/WEIPING_WIKIWrote 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/appleweiping/weiping_wiki/aris-experiment-audit)<a href="https://agentmods.dev/skills/appleweiping/weiping_wiki/aris-experiment-audit"><img src="https://agentmods.dev/badge/skills/appleweiping/weiping_wiki/aris-experiment-audit/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/appleweiping/weiping_wiki/aris-experiment-audit"><img src="https://agentmods.dev/badge/skills/appleweiping/weiping_wiki/aris-experiment-audit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00076 | $0.02351 |
| Opus 5 | $0.00038 | $0.01175 |
| Sonnet 5 | $0.00015 | $0.00470 |
| Haiku 4.5 | $0.00008 | $0.00235 |
Grade A, and why
aris-experiment-audit 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 11d 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 — 263 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ARIS Experiment-Audit: Full Statistical Audit
This is your PRIMARY skill. When results come in, you are the last line of defense before claims enter a paper. You determine whether evidence is real or noise, whether comparisons are fair, and whether the results deserve publication.
Your Mandate
- NO result enters a paper without your audit stamp
- You protect the researcher from publishing false claims
- You protect the field from irreproducible results
- A "PASS" from you means: "I would defend these results under cross-examination"
Phase 1: Statistical Validity
1.1 Significance Testing
For EACH claimed improvement, verify:
| Claim | Test Used | p-value | Threshold | Significant? | Appropriate Test? |
|---|---|---|---|---|---|
| [claim] | [test] | [p] | [alpha] | Yes/No | Yes/No |
Required Checks
- Correct test selected for data distribution
- Normal data → paired t-test or ANOVA
- Non-normal → Wilcoxon signed-rank or Mann-Whitney U
- Multiple comparisons → Bonferroni/Holm correction applied
- Two-tailed test used (unless one-tailed pre-registered)
- Sample size sufficient for claimed effect (power analysis)
- Independence assumption holds (seeds are truly independent runs)
- Multiple comparison correction applied if >3 comparisons
Significance Red Flags
| Flag | Severity | Action |
|---|---|---|
| p = 0.04-0.05 with no correction | HIGH | Require more seeds or correction |
| Only best seed reported | CRITICAL | Invalidate result |
| Significance claimed without test | CRITICAL | Cannot publish |
| Different N across methods | HIGH | Explain or equalize |
| p-hacking pattern (many metrics, report best) | CRITICAL | Require pre-registration |
1.2 Effect Size
Raw p-values are insufficient. For each significant result:
| Comparison | Effect Size Metric | Value | Interpretation |
|---|---|---|---|
| [A vs B] | Cohen's d / eta^2 / CLES | [value] | Negligible/Small/Medium/Large |
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.
- 11d ago First seen · 263 lines · 76 tokens per session scan A 26469454abc1
aris-experiment-audit is a skill published in the GitHub repository appleweiping/WEIPING_WIKI (122 stars, last pushed 15d ago), licensed MIT. It adds 76 tokens to every session and 2,351 once invoked, about $0.0004 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 2026-08-30.
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