self-correction-is-resilient-to-llm-unavailability
OUT derived (depth 6)
The system's core self-correction mechanisms — contradiction resolution through dependency-directed backtracking and staleness detection through source hash comparison — require no external dependencies and execute on stdlib alone, while all LLM-facing operations apply consistent fail-soft error handling — LLM unavailability degrades knowledge expansion but never compromises correction integrity.
Summary
Even if the LLM goes down, the system can still fix its own mistakes — contradiction resolution and staleness checks run entirely on local code with no external calls. LLM failures only limit the ability to generate new knowledge, never the ability to correct existing errors.
Justifications
SL — Zero-dependency self-correction plus fail-soft LLM integration means LLM unavailability cannot compromise system integrity
Antecedents (all must be IN):
- self-correction-requires-no-external-dependencies — The system's self-correction capabilities — contradiction resolution through dependency-directed backtracking and staleness detection through source hash comparison — operate entirely within a self-contained, safely-layered architecture with zero external dependencies, ensuring maintenance is never blocked by unavailable services, network failures, or broken supply chains
- llm-integration-fails-softly-across-modules — All LLM-facing modules apply consistent fail-soft error handling: the ask module always returns a string even when the LLM is unavailable, and the derive pipeline accumulates per-proposal errors rather than raising exceptions — no LLM failure path crashes the system.
Dependents
These beliefs depend on this one:
- fault-tolerance-spans-inspection-through-self-correction — Fault tolerance covers the complete belief quality spectrum: passive inspection operations (review, staleness checking, list-negative classification) degrade gracefully with fail-safe defaults and never mutate state, AND active self-correction (contradiction resolution via backtracking, staleness detection via source hashing) continues operating without external LLM dependencies — the system maintains quality assurance autonomously even when LLMs, external files, or network resources are unavailable.