/assumption-stress-test
Systematic stress testing of assumptions — surface, classify by vulnerability,
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill assumption-stress-test --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/assumption-stress-test
Context preview
The summary Claude sees to decide when to auto-load this skill.
Systematic stress testing of assumptions — surface, classify by vulnerability,
SKILL.md
assumption-stress-test.SKILL.mdname: assumption-stress-test
description: Systematic stress testing of assumptions — surface, classify by vulnerability,
attack, assess fragility. Combines assumption-surfacing (shared), abp-vulnerability-classification,
and clr-validation SOPs.
execution: tactic
dependencies:
sops:
- abp-vulnerability-classification
- clr-validation
- deep-insight-assumption-surfacing
- deep-insight-paper-research
Assumption Stress Test
Systematically stress-test assumptions to find dangerous ones.
Operations
- assumption-surfacing (shared) — extract all implicit assumptions
- abp-vulnerability-classification — classify by load-bearing × vulnerable
- clr-validation — validate causal logic of critical assumptions
Available SOPs
**Shared:** assumption-surfacing **Subagent:** abp-vulnerability-classification, clr-validation **Import:** paper-research
Execution Guidance
Surface all assumptions (shared SOP). Classify each by load-bearing × vulnerable matrix. Validate causal logic of most critical assumptions (High-Load × High-Vulnerable quadrant).
Minimum Yield
<HARD-GATE>
- assumptions surfaced: >= 5
- vulnerability classifications: >= 5
- CLR validations on critical assumptions: >= 2
- dangerous assumptions identified: >= 1
</HARD-GATE>
<!-- BEGIN available-tables (generated) -->
Available SOPs
Optional, no fixed order; the final leaf is always a sop.
| SOP | When to use | | --- | --- | | abp-vulnerability-classification | Classify assumptions on 2 axes — load-bearing (how much conclusion depends on it) × vulnerable (how likely to be false). Focuses attention on High-Load × High-Vulnerable quadrant. | | clr-validation | Apply Goldratt's 8 Categories of Legitimate Reservation to validate causal claims. Tests clarity, existence, sufficiency, and logical integrity. | | deep-insight-assumption-surfacing | Systematically extract implicit assumptions from methods, frameworks, or arguments. Identifies what is taken for granted without explicit justification. | | deep-insight-paper-research | Full-text paper reading via three-pass Keshav method. Import of literature-engine/literature-research skill. Authoritative source for claims about paper content. |
<!-- END available-tables (generated) -->
Read more
name: assumption-stress-test description: Systematic stress testing of assumptions — surface, classify by vulnerability, attack, assess fragility. Combines assumption-surfacing (shared), abp-vulnerability-classification, and clr-validation SOPs. execution: tactic dependencies: sops: - abp-vulnerability-classification - clr-validation - deep-insight-assumption-surfacing - deep-insight-paper-research
Assumption Stress Test
Systematically stress-test assumptions to find dangerous ones.
Operations
- assumption-surfacing (shared) — extract all implicit assumptions
- abp-vulnerability-classification — classify by load-bearing × vulnerable
- clr-validation — validate causal logic of critical assumptions
Available SOPs
**Shared:** assumption-surfacing **Subagent:** abp-vulnerability-classification, clr-validation **Import:** paper-research
Execution Guidance
Surface all assumptions (shared SOP). Classify each by load-bearing × vulnerable matrix. Validate causal logic of most critical assumptions (High-Load × High-Vulnerable quadrant).
Minimum Yield
<HARD-GATE> - assumptions surfaced: >= 5 - vulnerability classifications: >= 5 - CLR validations on critical assumptions: >= 2 - dangerous assumptions identified: >= 1 </HARD-GATE>
<!-- BEGIN available-tables (generated) -->
Available SOPs
Optional, no fixed order; the final leaf is always a sop.
| SOP | When to use | | --- | --- | | abp-vulnerability-classification | Classify assumptions on 2 axes — load-bearing (how much conclusion depends on it) × vulnerable (how likely to be false). Focuses attention on High-Load × High-Vulnerable quadrant. | | clr-validation | Apply Goldratt's 8 Categories of Legitimate Reservation to validate causal claims. Tests clarity, existence, sufficiency, and logical integrity. | | deep-insight-assumption-surfacing | Systematically extract implicit assumptions from methods, frameworks, or arguments. Identifies what is taken for granted without explicit justification. | | deep-insight-paper-research | Full-text paper reading via three-pass Keshav method. Import of literature-engine/literature-research skill. Authoritative source for claims about paper content. |
<!-- END available-tables (generated) -->
The complete research orchestration system for AI-native science. What It Does Design Philosophy Architecture (v3.2.2) Quick Start Configuration Roadmap License DARE is not a tool that helps you do research. It is the researcher.
Repo: yogsoth-ai/de-anthropocentric-research-engine
Other skills on de-anthropocentric-research-engine.
- /formated-results
Closing skill for the research-executor, loaded as the last step of formated-specs. Summarize the design just produced into one research-result JSON fenced block in your reply. Do not execute the research.
Open skill - /formated-specs
Spec-slot skill for the research-executor. Emit the 4-layer DARE orchestration of the assigned topic as one research-graph JSON fenced block in your reply. Replaces the generic spec-writing step.
Open skill - /injection-fidelity
Loss-1 judge (codex role). Given one sample's de-identified dialogue and its PolicyCard, decide axis-by-axis whether the user-simulator enacted the card's per-axis pressure. Judge enactment of the card, never whether the research is good.
Open skill - /ladder-quality-order
Loss-2 judge (codex role). Over one topic's 6 shuffled research-design samples, pairwise-rank by quality using the D1–D5 standard. Emit the pairwise log; the harness computes the order and the ladder verdicts. Judge quality difference, never against academic standards.
Open skill - /optimization-loop
The optimizer brain for the ladder-foundry pretraining loop. Runs the two-level nested batch loop, delegates gating to gate_eval, attributes a failing batch to one weight (attribute-first), and recovers from disk after compaction. Control flow is fully scripted; only the
Open skill - /acu-nugget-recall
Tactic: Extract atomic units from one paper and score how much of a caller-supplied summary covers. Use for ACU-style binary or Nugget-style ternary recall checks; cannot run without a target summary.
Open skill

