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 stress-test-dialectical-escalationgit 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/stress-test-dialectical-escalation)<a href="https://agentmods.dev/skills/yogsoth-ai/stress-test/stress-test-dialectical-escalation"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/stress-test/stress-test-dialectical-escalation/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/stress-test-dialectical-escalation"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/stress-test/stress-test-dialectical-escalation.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 | $0.00033 | $0.00577 |
| Opus 5 | $0.00016 | $0.00289 |
| Sonnet 5 | $0.00007 | $0.00115 |
| Haiku 4.5 | $0.00003 | $0.00058 |
Grade A, and why
stress-test-dialectical-escalation 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 — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Dialectical Escalation Tactic
Progressive pressure escalation — attack sophistication increases each round based on defender confidence.
Orchestration
- debate-critic generates attack at current escalation level
- debate-defender responds with counter-arguments
- debate-judge evaluates exchange, scores defender confidence (0.0–1.0)
- confidence-calibration determines next action:
- confidence > 0.7 → escalate to next level
- confidence 0.3–0.7 → repeat at same level with different angle
- confidence < 0.3 → defender collapsed, record vulnerability
- Repeat until max rounds reached or saturation detected
Escalation Levels
- L1 Surface: Factual accuracy, evidence quality, citation validity
- L2 Structural: Logical coherence, argument dependencies, internal consistency
- L3 Foundational: Core assumptions, paradigm fit, alternative explanations
Subagents Dispatched
- debate-critic (attack generation per level)
- debate-defender (response generation)
- debate-judge (round scoring)
- confidence-calibration (escalation decision)
Termination Conditions
- Max rounds exhausted (budget-dependent: 4/8/12)
- Defender confidence drops below 0.3 (collapsed)
- Saturation detected (no new attack vectors found)
- All escalation levels completed with confidence > 0.7 (survived)
Available SOPs
Optional, no fixed order; the final leaf is always a sop.
| SOP | When to use |
|---|---|
| confidence-calibration | Calibrates confidence scores based on debate progression. Determines whether to escalate, continue, or terminate based on cumulative evidence. |
| debate-critic | Generates structured criticism from attack stance using Toulmin model. Produces claims, grounds, warrants, and rebuttals targeting artifact weaknesses. |
| debate-defender | Responds to attacks with counter-evidence and counter-arguments. Defends artifact using evidence, clarification, and rebuttal while acknowledging valid criticisms. |
| debate-judge | Evaluates debate exchanges, adjudicates argument quality, and produces round verdicts with confidence scores and reasoning. |
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 · 66 lines · 33 tokens per session scan A 165b0cca085c
stress-test-dialectical-escalation is a skill published in the GitHub repository yogsoth-ai/stress-test (2 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 33 tokens to every session and 577 once invoked, about $0.0002 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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