Model Gap Detection

SOP for finding gaps in the causal model — missing variables, unexplained effects, weak links.

yogsoth-ai e221f61 946 B Updated

File contents

Model Gap Detection

Find gaps in the causal model: effects without causes, causes without mechanisms, weak confidence links.

Tool

vault_graph_stats + vault_query_graph

Protocol

  1. Run vault_graph_stats — identify orphans and low-connectivity nodes
  2. For each variable with out_degree=0 (no downstream effects): is this truly a terminal variable?
  3. For each variable with in_degree=0 (no upstream causes): is this truly exogenous?
  4. Check for edges with weight < 0.3 — these are weak links needing more evidence
  5. Report gaps with suggested actions

HARD-GATE

Yield

Returns: { unexplained_effects: string[], missing_causes: string[], weak_links: string[] }

yogsoth-ai/de-anthropocentric-research-engine/tree/main/skills/model-gap-detection commit e221f61548

Frequently asked questions

npx skillmds@latest add yogsoth-ai/model-gap-detection