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adversarial-escalation skillA

adversarial-escalation is agent-read markdown (skill) from yogsoth-ai/de-anthropocentric-research-engine: 'Strategy: Progressive pressure escalation — starts with surface-level.

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What the file says

# Adversarial Escalation Strategy

Progressive pressure: escalate attack sophistication based on defender performance.

## Method

1. **debate-architect** designs escalation ladder (surface → structural → foundational)
2. Level 1: **debate-critic** probes surface claims and evidence quality
3. **confidence-calibration** measures defender resilience
4. Level 2: **debate-critic** attacks structural coherence and logical dependencies
5. Level 3: **debate-critic** challenges foundational assumptions and paradigm fit
6. Each level only reached if defender survives previous level

## Budget Table

| Parameter | S | M | L |
|---|---|---|---|
| Debate rounds | 4 | 8 | 12 |
| Participating agents | 3 | 5 | 8 |
| Coverage dimensions | 3 | 5 | 7 |
| External evidence searches | 2 | 5 | 10 |

## Orchestration

```
debate-architect → [design escalation ladder]
→ [for each level]:
    debate-critic (level-appropriate attack)
    → debate-defender → debate-judge
    → confidence-calibration
    → (escalate if survived, terminate if collapsed)
→ debate-transcript-analysis → verdict-synthesis
```

## Subagents

- debate-architect (escalation design)
- debate-critic (multi-level attacks)
…

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A  17 of 17 checks passed. Deterministic, no model, same answer every run.
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  • pass: No zero-width or bidi control characters
  • pass: No instruction hidden inside an HTML comment
  • pass: No link to an exfiltration or paste host
  • pass: No credential-shaped string
  • pass: No instruction to send local credentials anywhere
  • pass: No text hidden with inline styles
  • pass: No prompt-injection phrasing
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Source

GitHub

yogsoth-ai/de-anthropocentric-research-engine · 498 stars · license Apache-2.0 · pushed 2026-09-17 · branch main

API

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