Adversarial Escalation Strategy

SkillDev tools

'Strategy: Progressive pressure escalation — starts with surface-level

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Adversarial Escalation Strategy skill

What this skill tells your AI

The instructions your AI receives, as published by yogsoth-ai/de-anthropocentric-research-engine in skills/adversarial-escalation/SKILL.md and read by ahel’s review.

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

ParameterSML
Debate rounds4812
Participating agents358
Coverage dimensions357
External evidence searches2510

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)
  • debate-defender (responses)
  • debate-judge (level adjudication)
  • confidence-calibration (escalation trigger)

Available Tactics

Optional, no fixed order; the final leaf is always a sop.

TacticWhen to use
stress-test-dialectical-escalationTactic: Progressive debate escalation based on confidence thresholds. Each round increases attack sophistication until defender collapses or proves resilient.

Available SOPs

Optional, no fixed order; the final leaf is always a sop.

SOPWhen to use
confidence-calibrationCalibrates confidence scores based on debate progression. Determines whether to escalate, continue, or terminate based on cumulative evidence.
debate-architectDesigns debate structure based on artifact type — selects attack vectors, assigns perspectives, determines escalation ladder, and configures round parameters.
debate-criticGenerates structured criticism from attack stance using Toulmin model. Produces claims, grounds, warrants, and rebuttals targeting artifact weaknesses.
debate-defenderResponds to attacks with counter-evidence and counter-arguments. Defends artifact using evidence, clarification, and rebuttal while acknowledging valid criticisms.
debate-judgeEvaluates debate exchanges, adjudicates argument quality, and produces round verdicts with confidence scores and reasoning.

Signals

GitHub stars
469
Forks
37
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
adversarial-escalation
Source
github.com/yogsoth-ai/de-anthropocentric-research-engine