cross-consistency-analysis
$
npx mdskill add yogsoth-ai/de-anthropocentric-research-engine/cross-consistency-analysisPairwise consistency checking (CCA) to reduce the total morphological solution space by 90-99%, leaving only internally consistent configurations.
SKILL.md
.github/skills/cross-consistency-analysisView on GitHub ↗
--- name: cross-consistency-analysis description: "CCA: pairwise consistency checking to reduce solution space 90-99%" execution: strategy used-by: morphological-exploration --- # Cross-Consistency Analysis Pairwise consistency checking (CCA) to reduce the total morphological solution space by 90-99%, leaving only internally consistent configurations. ## State Ledger | Resource | Target | Current | % | |----------|--------|---------|---| | web-search | 15 | 0 | 0% | | web-research | 5 | 0 | 0% | | paper-overview | 15 | 0 | 0% | | paper-search | 10 | 0 | 0% | | paper-research | 3 | 0 | 0% | ## HARD-GATE Cannot exit strategy until ≥80% of each budget line is consumed OR yield targets are met with justification for remaining budget. ## Available Tactics | Tactic | Role | |--------|------| | consistency-checking | Core tactic — evaluate and reduce | ## Available SOPs | SOP | Role | |-----|------| | consistency-pair-evaluation | Evaluate pairwise consistency judgments | | solution-space-reduction | Apply CCA to remove inconsistent combinations | | morphological-synthesis | Synthesize reduced space report | ## Execution Guidance 1. **Input matrix**: Receive morphological matrix from zwicky-box-construction or GMA 2. **Pair evaluation**: Run consistency-pair-evaluation on all parameter-value pairs 3. **Classify inconsistencies**: Tag as logical, empirical, or normative 4. **Reduce space**: Apply solution-space-reduction to eliminate inconsistent configurations 5. **Report**: Document reduction ratio and remaining viable space
More from yogsoth-ai/de-anthropocentric-research-engine
- abductive-hypothesis-generationStrategy: 面对异常的最佳解释推理
- ablation-brainstormRemove components one by one, observe system changes to reveal hidden dependencies and generate ideas from structural gaps.
- ablation-component-mappingMap system architecture to ablatable units for ablation studies
- ablation-designDesign ablation studies to isolate component contributions in ML systems
- ablation-executionRemove components one by one from a system, record the response/impact of each removal.
- abp-vulnerability-classificationClassify 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.
- abstraction-extractionExtract abstract principles from concrete domain cases. Strips domain-specific details to reveal transferable mechanisms.
- abstraction-ladderPerform bisociation at multiple abstraction levels
- abstraction-ladderingMove between concrete and abstract framings — 3 levels up (Why?) and 3 levels down (How?) to find the most productive research level.
- abstraction-to-designAbstract biological principle to design principle. Bridge from biology to engineering.