parameter-space-construction
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npx mdskill add yogsoth-ai/de-anthropocentric-research-engine/parameter-space-constructionConstructs parameter space by identifying drivers and enumerating values
- Solves the problem of defining a structured space for scenario planning
- Depends on scenario-driver-identification and parameter-enumeration tactics
- Validates driver independence, coverage, and abstraction level before proceeding
- Returns a validated Zwicky Box matrix with configuration space metrics
SKILL.md
.github/skills/parameter-space-constructionView on GitHub ↗
--- name: parameter-space-construction description: "Orchestrates driver identification and parameter enumeration to build the complete morphological field" version: 1.0.0 category: experiment-execution type: tactic used-by: scenario-planning orchestrates: - scenario-driver-identification - parameter-enumeration --- # Tactic: Parameter Space Construction ## Orchestration Pattern 1. **Spawn driver identification** → `scenario-driver-identification` - Pass: research context, planning horizon, domain constraints - Receive: ranked list of 5-8 uncertainty drivers with descriptions 2. **Validate driver set** - Check: Are drivers independent? (no redundancy) - Check: Do drivers span PESTEL categories? (no blind spots) - Check: Are drivers at the right abstraction level? (not too broad, not too narrow) - If validation fails: re-spawn with refined instructions 3. **Spawn parameter enumeration** → `parameter-enumeration` - Pass: validated driver list, MECE requirement, value count guidance (2-4 per driver) - Receive: complete Zwicky Box (driver × value matrix) 4. **Validate parameter space** - Check: Are values mutually exclusive within each driver? - Check: Are values collectively exhaustive within each driver? - Check: Is the total configuration space manageable? (< 500 combinations) - If validation fails: re-spawn enumeration with tighter constraints 5. **Compute space metrics** - Total configurations: product of all value counts - Expected surviving configs after CCA: ~10-20% of total - Estimated downstream budget: configs × per-scenario cost ## Quality Checks - [ ] All drivers are genuinely uncertain (not predetermined) - [ ] No driver is a subset or consequence of another - [ ] Values within each driver are truly MECE - [ ] Total space is computationally tractable for CCA - [ ] Parameter space covers the planning horizon adequately