factor-enumeration
$
npx mdskill add yogsoth-ai/de-anthropocentric-research-engine/factor-enumerationEnumerates all key factors, conditions, and assumptions supporting an artifact's conclusion.
- Identifies dependencies and assumptions in conclusions for deeper analysis.
- Uses subagent execution to ensure comprehensive and unbiased factor scanning.
- Analyzes input artifact and optional causal claims to extract relevant factors.
- Returns structured list of factors with types, importance, and categorization.
SKILL.md
.github/skills/factor-enumerationView on GitHub ↗
---
name: factor-enumeration
description: List all key factors, conditions, and assumptions that support or enable the artifact's conclusion.
execution: subagent
prompt: ./prompt.md
input: artifact (string), causal_claims (list)
used-by: [counterfactual-probing]
---
# Factor Enumeration
Lists all factors that the conclusion depends on — explicit conditions, implicit assumptions, and background requirements.
## Execution
Subagent — spawned via subagent-spawning/spawn-agent.
## Why Subagent
Comprehensive factor enumeration requires systematic scanning without being biased by which factors seem most important.
## Input
- **artifact**: The artifact to analyze
- **causal_claims**: Previously extracted causal claims (optional)
## Output
- **factors**: List of {name, type, explicit/implicit, suspected_importance}
- **factor_count**: Total factors identified
- **categories**: Grouping of factors by type
## Budget
One unit = one enumeration pass per artifact.