Propagate input uncertainties through the model via Monte Carlo sampling. Identifies which input uncertainties contribute most to output uncertainty.
Scanned 5/27/2026
Install via CLI
openskills install yogsoth-ai/de-anthropocentric-research-engine---
name: uncertainty-propagation
description: Propagate input uncertainties through the model via Monte Carlo sampling. Identifies which input uncertainties contribute most to output uncertainty.
used-by: sensitivity-analysis
---
# Uncertainty Propagation
Map how input uncertainty flows to output uncertainty.
## Budget
| Base SOP | Target | ±10% Range |
|----------|--------|------------|
| web-search | 20 | 18–22 |
| web-research | 10 | 9–11 |
| paper-overview | 25 | 22–28 |
| paper-search | 20 | 18–22 |
| paper-research | 10 | 9–11 |
## State Ledger
```
<HARD-GATE>
| SOP | Done | Target | % |
|-----|------|--------|---|
| web-search | ? | 20 | ? |
| web-research | ? | 10 | ? |
| paper-overview | ? | 25 | ? |
| paper-search | ? | 20 | ? |
| paper-research | ? | 10 | ? |
Budget Gate: OPEN/CLOSED (>=80% required to exit)
</HARD-GATE>
```
## Available Tactics
- uncertainty-cascade
## Available SOPs
**Import:** web-search, web-research, paper-overview, paper-search, paper-research
**Subagent:** distribution-assignment, monte-carlo-sampling, critical-path-identification
## Execution Guidance
Assign probability distributions to uncertain inputs, propagate through the model via Monte Carlo sampling, analyze output distribution, identify which input uncertainties contribute most.
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