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/de-anthropocentric-research-engine --skill adversarial-stress-testinggit clone --depth 1 https://github.com/yogsoth-ai/de-anthropocentric-research-engineWrote 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/de-anthropocentric-research-engine/adversarial-stress-testing)<a href="https://agentmods.dev/skills/yogsoth-ai/de-anthropocentric-research-engine/adversarial-stress-testing"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/de-anthropocentric-research-engine/adversarial-stress-testing/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/de-anthropocentric-research-engine/adversarial-stress-testing"><img src="https://agentmods.dev/badge/skills/yogsoth-ai/de-anthropocentric-research-engine/adversarial-stress-testing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Prompt Injection · line 84 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
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 | $0.00069 | $0.01247 |
| Opus 5.5 | $0.00028 | $0.00499 |
| Sonnet 5.5 | $0.00014 | $0.00249 |
| Haiku 4.5 | $0.00007 | $0.00125 |
Grade A, and why
adversarial-stress-testing 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 1mo 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- adversarial-stress-testing — 91% identical, 2 lines differ
How it starts
The opening of the file, as written. The whole thing — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Adversarial Stress Testing
Core Question: Does this artifact collapse under logical limits and boundary conditions?
Methodology Sources
- Lakatos (1976) — Proofs and Refutations: counterexample-driven refinement
- Dutilh Novaes (2016) — Adversarial argumentation as dialogical practice
- Clarke BVA — Boundary Value Analysis for systematic edge testing
- Flyvbjerg (2006) — Critical case methodology: most-likely/least-likely selection
- Popper (1959) — Falsificationism: seek conditions where claims break
Strategy Routing
| Artifact Type | Primary Strategy | Rationale |
|---|---|---|
| claim, hypothesis | assumption-negation | Direct logical attack |
| gap, research-question | lakatos-heuristics | Counterexample refinement |
| idea, approach | boundary-enumeration | Parameter space testing |
| experiment-design | critical-case-design | Decisive test selection |
| any (synthesis) | validity-envelope-mapping | Comprehensive envelope |
Budget Table
| Resource | S | M | L |
|---|---|---|---|
| Negation derivation chains | 3 | 6 | 10 |
| Counterexamples/boundary cases | 5 | 12 | 25 |
| Parameter dimensions | 3 | 6 | 10 |
| Validity envelope dimensions | 2 | 4 | 6 |
Tactics
- contradiction-derivation — Negate, derive, detect contradiction
- boundary-probing — Map parameter space, test extremes, find breakpoints
- counterexample-heuristics — Generate monsters, bar or incorporate
Context Management
- Persist derivation chains and counterexamples across rounds
- Track which negations produced genuine contradictions vs. benign outcomes
- Accumulate validity envelope boundaries incrementally
Output
Produces AdversarialStressReport containing: identified breakpoints, validity envelope, surviving refined claims, and confidence assessment.
Available Strategies
Optional, no fixed order; the final leaf is always a sop.
| Strategy | When to use |
|---|---|
| assumption-negation | Classic reductio ad absurdum: negate the core claim, derive logical consequences, seek contradiction or absurdity. |
| boundary-enumeration | Systematic Boundary Value Analysis: identify parameter boundaries, test at and beyond limits, detect breakpoints. |
| critical-case-design | Flyvbjerg critical case methodology: select most-likely and least-likely cases to maximize inferential power. |
| lakatos-heuristics | Proofs and Refutations method: generate counterexamples, attempt monster-barring, incorporate surviving counterexamples as lemma refinements. |
| stress-test-validity-envelope-mapping | Map the complete validity envelope of a claim across all relevant dimensions, synthesizing breakpoints into a bounded region. |
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.
- 1mo ago First seen · 122 lines · 69 tokens per session scan A 7a9ff39166a2
adversarial-stress-testing is a skill published in the GitHub repository yogsoth-ai/de-anthropocentric-research-engine (505 stars, last pushed 5d ago), licensed Apache-2.0. It adds 69 tokens to every session and 1,247 once invoked, about $0.0003 per session on Opus 5.5. 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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