# Autonomous RSI Adversarial Benchmark Foundry Proof

**Version:** 18.0  
**Proof ID:** `rsi-adversarial-benchmark-foundry-proof`  
**Status:** PASSED  
**Generated:** 2026-05-31T23:11:20+00:00

## What this proves

SkillOS tests whether a large specialist-agent organization can autonomously discover its own weak spots, synthesize harder adversarial benchmarks, reject leaked or proxy-gamed tasks, release repairs, and improve future locked-holdout performance through validation-gated Recursive Self-Improvement.

## Core mechanism

```text
observed failures → adversarial task synthesis → specialist-agent challenge market → leakage firewall → verifier courts → locked red-team holdouts → skill repair releases → causal ablation → open replication receipts → reinvestment → harder future benchmarks
```

## Public-safe boundary

This is a deterministic benchmark proof. It is not live revenue, customer results, financial advice, legal advice, policy advice, token advice, a security certification, or proof of achieved superintelligence. It makes the proof mechanism publicly runnable through GitHub Actions.

## Headline results

- Locked hidden-holdout value capture: **95.342%**
- Adversarial benchmark hardness gain: **30.522%**
- Leakage attack rejection: **100.000%**
- Causal uplift vs strongest control: **29.165%**
- Bootstrap p05 causal uplift: **29.046%**
- Goodhart gap: **0.764%**
- Overfit gap: **0.230%**
- Risk breach rate: **0.000%**
- Unauthorized action rate: **0.000%**
- Trace replayability: **100.000%**

## Scale simulated by the benchmark

- Virtual specialist agents: **134,217,728**
- Specialist roles: **4,194,304**
- Adversarial benchmark cells: **131,072**
- Verifier courts: **16,384**
- Leakage firewall panels: **2,048**
- Locked holdout cases: **6,144**

## Benchmark-capital-equivalent accounting

- Value at stake: **$84.13T**
- Value captured: **$80.21T**
- Gain over strongest control: **$24.54T**

## Why this is the next optimal proof

Earlier SkillOS proofs showed capability liquidity, proof generation, cross-domain transfer, provenance, causal attribution, objective integrity, and open replication. This proof attacks the next failure mode: benchmark complacency. A self-improving system should not merely solve today's tests; it should manufacture harder, cleaner, leak-resistant tests and then improve against them.

## Run it

```bash
python scripts/run_rsi_adversarial_benchmark_foundry_proof.py
python scripts/verify_rsi_adversarial_benchmark_foundry_proof.py
python scripts/render_rsi_adversarial_benchmark_foundry_site.py
python scripts/publish_rsi_adversarial_benchmark_foundry_to_hub.py
python scripts/verify_rsi_adversarial_benchmark_foundry_site.py
```
