safe

29 beliefs (22 IN, 7 OUT)

• IN belief-replacement-is-topology-safe-and-view-consistent
  Both belief replacement mechanisms achieve topology safety and view consistency: supersession operates through reversible outlist semantics with gated view exclusion of superseded nodes, while deduplication rewires all justification references (both antecedent and outlist) to the most-connected survivor with user-auditable plans — ensuring the dependency graph remains structurally sound and consumers see a clean non-redundant belief set regardless of which replacement mechanism was used.
• IN bidirectional-modification-is-richly-governed-and-exception-safe
  Every bidirectional belief modification — contradiction resolution through traceable backtracking and defeat reversal with guided recovery — operates within richly-governed exception-safe revision that manages state beyond binary truth values, so every modification in either direction produces metadata-enriched recoverable state changes within a deterministic lifecycle.
• IN both-backends-support-safe-hypothetical-reasoning
  Both storage backends enable hypothetical what-if reasoning without permanent mutation: PgApi performs real mutations inside a transaction then rolls back, while the in-memory backend uses write-flag gating to discard speculative changes after analysis
• IN challenge-defense-is-crash-safe
  The dialectical challenge/defend system reaches correct truth states through recursive outlist injection evaluated by deterministic terminating propagation.
• OUT determinism-enables-safe-dialectical-extension
  Dialectical transformation is operationally safe precisely because it composes with the minimal deterministic engine — the irreversible premise-to-justified conversion inherits deterministic propagation and uniform evaluation, so dialectics need no dedicated safety machinery beyond what the core already provides.
• IN dialectical-revision-is-exception-safe-with-rich-traceable-state
  Dialectical revision — deterministic, reliable, and semantically complete — simultaneously governs metadata-enriched traceable state (retraction flags, stale reasons, access tags, supersession) AND operates within an exception-safe richly-governed framework, ensuring that all dialectical operations produce rich auditable state transitions with safe failure recovery across all revision mechanisms.
• OUT dialectical-transformation-is-operationally-safe
  The irreversible premise-to-justified transformation during challenge is both semantically safe (inherits uniform outlist evaluation and truth maintenance properties from the dialectical structure) and operationally safe (executes within atomic load/save transactions with deterministic BFS propagation).
• OUT external-beliefs-are-safe-and-current
  External beliefs are managed end-to-end across their complete lifecycle with no gap between ingestion safety and ongoing maintenance: defensively contained at ingestion through layered validation, correctly lifecycle-managed through import reconciliation and staleness checking, and actively tracked for currency — no external belief enters unvalidated, drifts undetected, or persists without lifecycle oversight.
• OUT external-integration-is-architecturally-safe
  External beliefs are end-to-end safe within the system's architecture: defensively contained at ingestion and lifecycle-managed thereafter (external belief thread) within the same three-layer boundaries and atomic mutation guarantees that protect internal operations (architecture thread).
• IN initialization-is-safe-and-path-independent-across-backends
  System initialization produces identical belief states regardless of both initialization path (stored-state bootstrap vs deterministic reasoning) and storage backend (SQLite vs PostgreSQL providing equivalent safety through backend-appropriate mechanisms), eliminating all bootstrap-time variation
• IN metadata-governance-flows-through-safe-topology
  Metadata-carried lifecycle state (retraction flags, stale reasons, access tags) actively governs truth propagation that is itself topology-complete and inconsistency-safe — lifecycle decisions propagate through all transitive dependencies including outlist-connected paths, even in the presence of dangling references, without runtime errors.
• OUT operational-profile-is-safe-assured-and-resource-bounded
  The system's complete operational profile achieves both safety (defense-in-depth reinforced across LLM and system boundaries with resource-efficient layered defenses) and assurance (spanning temporal self-correction, end-to-end reliability, and external control within efficient pipeline bounds) — neither safety nor assurance requires resource trade-offs against the other.
• IN propagation-is-safe-and-terminating
  Truth propagation is both lifecycle-safe and guaranteed to terminate: retracted nodes are skipped, trigger nodes are never recomputed, BFS prevents stack overflow, and stop-on-unchanged prevents oscillation — propagation respects every node state it encounters.
• IN propagation-is-safe-under-graph-inconsistency
  Truth propagation achieves correctness even when the dependency graph contains dangling references: missing nodes are skipped with structured warnings rather than crashing, dangling IDs are excluded from both the changed and visited sets, and this graceful degradation composes with the underlying termination and lifecycle-awareness guarantees for all reachable nodes.
• IN review-output-is-uniform-and-fail-safe
  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.
• 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.
• IN review-parse-defaults-safe
  When the LLM response is missing fields, `parse_review_response` defaults to `valid=True`, `sufficient=True`, `necessary=True` — a parse error never generates a false-positive validity warning.
• IN review-pipeline-is-scoped-and-mutation-safe
  The belief review pipeline restricts evaluation to derived beliefs only (premises excluded) and gates auto-retraction behind the dry-run flag, ensuring review operations are scope-limited and mutation-safe by default.
• IN revision-is-exception-safe-and-recoverable
  Every revision mechanism — whether normal (outlist defeat, dialectical challenge/defend) or exceptional (contradiction-triggered backtracking, graph inconsistency) — is simultaneously safe (handled without crashes or corruption), traceable (producing deterministic artifact trails), and recoverable (providing guided restoration hints for cascade victims) — the system never enters an unobservable or unrecoverable state regardless of failure mode.
• IN revision-is-richly-governed-and-exception-safe
  The belief revision system simultaneously governs state richer than binary truth values — metadata-enabled lifecycle management including retraction reasons, staleness markers, and access tags — while remaining exception-safe and recoverable under all failure conditions, ensuring that metadata-carried lifecycle state is never corrupted by exceptions.
• OUT revision-is-universally-safe
  The complete revision system has no blind spots: every belief — including all semantic edge cases (vacuous premises, asymmetric absence, empty antecedents) — can be revised through either reactive or proactive paths while preserving semantic identity and respecting node lifecycle states.
• IN rich-governance-is-exception-safe
  The system's rich lifecycle governance — deterministic, lifecycle-complete, extending beyond binary truth to metadata-enabled state with full monitoring — operates within an exception-safe framework spanning both TMS core and source lifecycle: contradictions are resolved through deterministic backtracking, challenges reach correct truth states through crash-safe propagation, and source failures degrade gracefully through fail-safe path resolution — ensuring that rich state transitions never produce corrupted or inconsistent lifecycle metadata.
• OUT safe-universal-revisability
  Any mutation source — human dialectical challenge, LLM-derived proposal, or multi-agent import — can safely revise any belief in the network through complete minimal mechanisms; the system imposes no restrictions on who can revise what, while guaranteeing that every revision path preserves consistency.
• IN source-pipeline-is-end-to-end-fail-safe
  The complete source integrity pipeline from path resolution through hash computation to staleness detection is end-to-end fail-safe: convention-based resolution returns None on missing files rather than raising exceptions, collision-resistant SHA-256 hashing backfills additively without overwriting, and staleness detection catches all drift with CI-ready exit codes — no stage in the pipeline raises exceptions on adverse conditions, and each stage's output gracefully feeds the next.
• IN source-resolution-is-convention-based-and-fail-safe
  Source path resolution follows a convention-based repo-alias/relative-path format and returns None on missing files rather than raising exceptions, providing safe path resolution for the staleness checking pipeline.
• IN source-tracking-is-collision-resistant-and-safe
  Source integrity tracking uses full 64-character SHA-256 digests with exact string comparison for collision resistance, and backfills hashes additively without overwriting existing values — ensuring high-fidelity drift detection with no accidental data loss
• IN storage-layer-is-backend-agnostic-and-safe
  Both storage backends provide equivalent safety guarantees through backend-appropriate mechanisms: atomic isolated mutations (context-managed load/save for SQLite, per-method transactions for PgApi) and safe hypothetical reasoning (write-flag gating for SQLite, transaction rollback for PgApi), making safety properties independent of backend choice.
• IN sync-is-safe-for-automated-reconciliation
  `sync_agent` can be safely re-run on any schedule — idempotent execution with cascade structure preservation means repeated automated synchronization never corrupts outlist-based justification hierarchies or produces accumulating side effects.
• IN tms-core-is-crash-safe
  The TMS core provides crash-free truth maintenance: deterministic termination, pure evaluation, and conservative failure semantics ensure correct results across all reachable nodes.