review-output-is-uniform-and-fail-safe
IN derived (depth 1)
Review response parsing defaults missing fields to passing, accepts only JSON arrays as valid input, and normalizes every result to a guaranteed six-key schema — producing uniform fail-safe structured output regardless of LLM response quality.
Summary
When the system parses review responses from the LLM, it is designed to never produce a false negative from bad output. If the LLM returns malformed JSON, missing fields, or unexpected structure, the parser either drops the result entirely or fills in defaults that assume everything is fine. This means the review pipeline will never incorrectly flag a belief as invalid just because the LLM had a bad day — the cost is that genuinely problematic beliefs might slip through unnoticed rather than causing spurious errors.
Justifications
SL — All review parsing behaviors converge on uniform fail-safe output with strict input and normalized schema
Antecedents (all must be IN):
- review-parse-defaults-fail-safe — `parse_review_response` defaults `valid`, `sufficient`, and `necessary` to `True`, so a missing or malformed field in LLM output never triggers a false alarm.
- review-parse-requires-json-array — `parse_review_response` only accepts JSON arrays; a bare JSON object `{...}` is treated as unparseable and returns an empty list — the LLM must return a list even for single-item reviews.
- review-result-schema-is-normalized — Every result dict returned by `parse_review_response` is guaranteed to have exactly six keys (`id`, `valid`, `sufficient`, `necessary`, `unnecessary_antecedents`, `comment`) regardless of what the LLM returned, via normalization with safe defaults.
Dependents
These beliefs depend on this one:
- inspection-outputs-are-uniformly-normalized — Both inspection mechanisms — belief review and staleness checking — produce normalized, schema-consistent, fail-safe output with deterministic structure suitable for automated consumption.
- review-achieves-verified-fault-tolerance — The review pipeline's scoped mutation-safe operation combined with uniform fail-safe output achieves verified fault tolerance across all failure modes — batch failures, missing antecedent references, and malformed LLM responses.