Audit each schema's implicit assumptions, then…

For each schema, list assumptions it makes—things it takes for granted without defining—then compare assumption lists across schemas to find shared dependency gaps where both schemas assume the same foundational concept but neither defines it.

When This Fires

During schema integration when combining frameworks from different domains
When evaluating the robustness of a mental model — its assumptions are its vulnerability surface
When looking for high-leverage learning targets (shared dependencies are the highest leverage)
During periodic knowledge system audits when checking for implicit foundation gaps

Common Failure Mode

Listing only the assumptions you're aware of rather than the ones the schema actually makes. The hardest assumptions to surface are the ones so fundamental you don't recognize them as assumptions: "time is linear," "people respond to incentives," "complex systems are decomposable." To find these, ask: "In what context would this schema completely fail?" The answer reveals assumptions that are so baked in they're invisible.

The Protocol

(1) For a schema in your knowledge system, list everything it takes for granted without defining. Ask: "What must be true for this schema to work?" and "What concepts does it use without explaining?" (2) Repeat for other schemas you want to compare. (3) Cross-compare: which assumptions appear in multiple schemas? These shared dependencies are your highest-leverage gaps. (4) For each shared dependency: is it explicitly defined somewhere in your knowledge system? If not → create that definition. You've found a foundational concept that multiple frameworks depend on but none examines. (5) Check whether any shared assumption is questionable — if multiple schemas depend on an assumption that may not hold, you've found a systemic vulnerability.