feat(phase5): epistemic confidence model - #137
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Calibrated uncertainty levels (established/provisional/contested/inferred) on warm-tier memories with auto-promotion via new sleep cycle Phase 5.12. New columns: epistemic_status, evidence_count, last_corroborated_at on warm_tier. New endpoint GET /memory/:id/epistemic and MCP tools memforge_certainty + memforge_epistemic_profile. Phase 5.12 promotes provisional rows with evidence_count >= 3 and multi-namespace positive retrievals to established, stamps last_corroborated_at, and demotes stale established rows back to provisional. Epistemic filter on query() restricts results to the desired confidence tier. TypeScript SDK, Python SDK, tool-definitions, and OpenAPI spec updated. Migration: schema/migration-v3.9.sql Split from #129 (PR-B of 6). Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This was referenced Jul 26, 2026
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The final Phase 5 slice — the Feature 1 remnant that never landed with PR #137. Phase 2.5 conflict resolution stops encoding noise as fact. - When the multi-factor score gap between two conflicting live memories is at most one point (one factor's worth of noise on the quantized integer scale), both are marked epistemic_status='contested' and the conflict resolves with a contested(...) strategy and no winner. The umbrella used a relative 20% threshold, which inverts on small integer scores (pure-noise 1-vs-0 reads as decisive, well-evidenced 6-vs-5 as contested) and is distorted by the mutual +100 supersession offset — the absolute delta is immune to both. - Superseded rows never contest: supersession is an absolute signal, and marking stale facts contested would resurface them as live disputes. - Contested is not terminal (the trap this same stack fixed for 'inferred'): Phase 5.12 promotes contested rows that earn the corroboration bar, and a decisive re-resolution of the dispute clears the winner's badge back to provisional. - tests/contested-conflicts.test.ts: 9 tests — close-call semantics, the exact one-vs-two-point boundary, winner/loser path preservation incl. untouched winner confidence, both-superseded decisiveness, contested recovery via decisive re-resolution. Conflict pairs share an identical relative timestamp (separate INSERTs see different now(), silently handing one side the +3 recency factor). - tests/epistemic-confidence.test.ts: the promotion tests now pin the new behavior (corroborated contested rows promote; uncorroborated ones stay). Claude-Session: https://claude.ai/code/session_011xCqQo49d3CEbn6oEvb3Ru Co-authored-by: Claude Fable 5 <noreply@anthropic.com>
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* feat(phase5): explainable memory operations (v3.10) Feature 2 of the Phase 5 split (umbrella #129): every retrieval can say why, and any warm memory can be asked where it stands. - query(): opt-in explain=true attaches ExplanationFactor[] per result (rank_score, epistemic_status weight, search_mode, temporal_decay) - explainMemory() + GET /memory/:id/explain?warm_id= reports scores, access patterns, and standing against the sleep-cycle score thresholds. Flags are scoped honestly (would_evict_by_threshold, would_flag_low_confidence): capacity eviction and the outcome / contradiction revision channels depend on live cross-table state and are deliberately not predicted here. - memforge_explain MCP tool wired to the real client method; TS + Python SDKs including both resilient wrappers; OpenAPI entries - query cache key extracted to queryKey() in cache.ts so the explain flag's participation in the key is unit-testable without Redis - warm_id validated to int8 range at REST and MCP boundaries; invalid agent ids on /explain return 400 like sibling routes No schema migration — pure code feature. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_011xCqQo49d3CEbn6oEvb3Ru * feat(phase5): causal memory graph (v3.10) Feature 3 of the Phase 5 split (umbrella #129): MemForge learns which events tend to follow which, and can answer "what led here" and "what happens next". - causal_edges table (migration-v3.10.sql + canonical schema, RLS, agent-scoped FKs to warm_tier with CASCADE) - Sleep Phase 6.1 mines memory_sequences for repeated content-level A→B patterns (md5 of 50-char prefixes, the Phase 5.5 technique) — the umbrella's row-pair grouping was unsatisfiable under the table's UNIQUE constraint and could never mine an edge. One edge per pattern, anchored to the earliest surviving pair so re-mining updates in place and FK cascade self-heals evicted anchors. Not skip-gated: the phase's input accumulates independently of its own change history, so the zero-change gate would permanently disable mining for young agents. Count surfaces as SleepCycleResult.causal_edges_updated. - getCausalChain(): recursive CTE traversal (causes|effects, depth clamped 1-10, 50-row cap, ordered depth then strength) - predict(): context match → outgoing edges → ranked events. probability = confidence × (1 − e^(−strength/30)) — monotonic, never saturated (raw strength × confidence clamps to 1.0 for virtually every mined edge). Shared-pool matches are excluded from the cause-id list (different id space than warm_tier), and effects are confined to the requested namespace. - GET /memory/:id/causal + POST /memory/:id/predict, memforge_causal_chain + memforge_predict MCP tools wired to real client methods, TS + Python SDKs incl. resilient wrappers, tool-definitions, OpenAPI - tests/causal-graph.test.ts: 39 tests (traversal incl. cycles/clamps/ cap/ordering, predict incl. namespace + pool-collision, Phase 6.1 mining incl. cv weighting + anchor stability + true re-confirmation step, pruning, HTTP status paths, migration shape + RLS) Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_011xCqQo49d3CEbn6oEvb3Ru * feat(phase5): hierarchical abstraction engine (v3.11) Feature 4 of the Phase 5 split (umbrella #129): Sleep Phase 5.11 distills cross-cutting principles from accumulated meta-reflections into a queryable abstractions store. - abstractions table (migration-v3.11.sql + canonical schema): level CHECK (principle|strategy|mental_model), stored md5 content_hash with UNIQUE (agent_id, level, namespace, content_hash) — the umbrella's ON CONFLICT DO NOTHING had no conflict target and would have duplicated every principle every cycle. RLS + grants. - Phase 5.11: gated on LLM presence, token budget, and >= 3 meta-reflections; prompt carries the codebase-standard injection guard, wraps reflection content via wrapUserContent, and states the schema's own limits (max 10, under 2000 chars, empty-array escape) so one overlong item does not sink the batch silently. Re-derivation is corroboration: ON CONFLICT keeps GREATEST confidence and revives a deactivated principle only when the fresh derivation is confident (>= 0.5); the conditional WHERE keeps change counts honest. Age-based deactivation of stale sub-0.2 principles. Not skip-gated (input accumulates independently). Cancellation checkpoint before the LLM call so canceled dream runs stop paying. runPhase now records real per-phase token spend in sleep_phase_analytics; count surfaces as SleepCycleResult.principles_extracted. - getAbstractions()/getPrinciples(), GET /principles + /abstractions routes, memforge_principles + memforge_mental_models MCP tools wired to real client methods (honest description: only 'principle' is auto-extracted today), TS + Python SDKs incl. resilient wrappers, tool-definitions, OpenAPI with shared Abstraction component. - tests/abstractions.test.ts: 39 tests — read paths, extraction incl. dedup/revival/confidence-raise/skip-gate immunity/token attribution/ budget + window gates/malformed + schema-invalid + missing-key LLM output, deactivation age and scope boundaries, ordering tiebreak, HTTP status paths, migration shape + RLS. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_011xCqQo49d3CEbn6oEvb3Ru * feat(phase5): cross-agent transfer learning bootstrap (v3.12) Feature 7 of the Phase 5 split (umbrella #129), the final feature: bootstrap a new agent from an experienced one. - bootstrapAgent(): one atomic transaction copying established warm memories (as epistemic 'inferred', 0.5x importance/confidence, _transferred_from provenance), active procedures, and active principles from source to target. Set-based INSERT..SELECT with dedup BEFORE each LIMIT so already-carried knowledge frees its cap slot (the umbrella looped N+1 with no-op ON CONFLICTs — procedures has no unique constraint at all). Memory dedup is namespace-scoped and content-exact (organic rows hash content differently, so equality is the only honest check). Warm-tier creates carry hash-chained audit records ('bootstrap' trigger) like consolidation and cold-restore do. - Phase 5.12 promotion now also considers 'inferred' rows meeting the same evidence bar — bootstrap is the first mass writer of inferred status, which was previously terminal: excluded by every epistemic filter except 'all' with no path out regardless of corroboration. - POST /memory/:id/bootstrap (path agent = target; Zod-validated body incl. agent-id regex and 0-1000/0-100 caps), memforge_bootstrap MCP tool with its own agent-pair validation and a real executor, TS + Python SDKs incl. resilient wrappers, tool-definitions, OpenAPI. Docs state honestly: principles carry no provenance marker (no metadata column); transferred rows are FTS-searchable immediately, semantic after embedding backfill, filter-visible after promotion. - No schema migration (audit trigger comment updated in schema.sql). - tests/bootstrap.test.ts: 22 tests — transfer semantics per category, discounts + provenance, namespace scoping incl. the cross-namespace dedup regression, per-category caps incl. principle slot-starvation regression, idempotency, organic-content dedup, transaction rollback via sabotage trigger, inferred->established promotion, auto-register, HTTP status paths. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_011xCqQo49d3CEbn6oEvb3Ru * feat(phase5): contested status for close-call conflict resolution (#166) The final Phase 5 slice — the Feature 1 remnant that never landed with PR #137. Phase 2.5 conflict resolution stops encoding noise as fact. - When the multi-factor score gap between two conflicting live memories is at most one point (one factor's worth of noise on the quantized integer scale), both are marked epistemic_status='contested' and the conflict resolves with a contested(...) strategy and no winner. The umbrella used a relative 20% threshold, which inverts on small integer scores (pure-noise 1-vs-0 reads as decisive, well-evidenced 6-vs-5 as contested) and is distorted by the mutual +100 supersession offset — the absolute delta is immune to both. - Superseded rows never contest: supersession is an absolute signal, and marking stale facts contested would resurface them as live disputes. - Contested is not terminal (the trap this same stack fixed for 'inferred'): Phase 5.12 promotes contested rows that earn the corroboration bar, and a decisive re-resolution of the dispute clears the winner's badge back to provisional. - tests/contested-conflicts.test.ts: 9 tests — close-call semantics, the exact one-vs-two-point boundary, winner/loser path preservation incl. untouched winner confidence, both-superseded decisiveness, contested recovery via decisive re-resolution. Conflict pairs share an identical relative timestamp (separate INSERTs see different now(), silently handing one side the +3 recency factor). - tests/epistemic-confidence.test.ts: the promotion tests now pin the new behavior (corroborated contested rows promote; uncorroborated ones stay). Claude-Session: https://claude.ai/code/session_011xCqQo49d3CEbn6oEvb3Ru Co-authored-by: Claude Fable 5 <noreply@anthropic.com> --------- Co-authored-by: Claude Fable 5 <noreply@anthropic.com>
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Summary
Second of six PRs splitting #129. Ships Feature 1: Epistemic Confidence Model — calibrated uncertainty levels on warm-tier memories with auto-promotion via sleep cycle.
What lands
warm_tier:epistemic_status TEXT NOT NULL DEFAULT 'provisional',evidence_count INTEGER NOT NULL DEFAULT 1,last_corroborated_at TIMESTAMPTZ. Indexwarm_tier_epistemic_idxon(agent_id, epistemic_status).run()loop after deprecated decay, before drift snapshot. Promotesprovisional → establishedwhen bothevidence_count >= 3AND positive retrievals come from ≥2 distinct namespaces (cross-context corroboration required). Stampslast_corroborated_at. Does NOT touchcontestedrows.query({ epistemic: 'established' })or array form filters retrieval by status.GET /memory/:agentId/epistemicreturns per-status counts.memforge_certainty(filtered query) andmemforge_epistemic_profile(counts).epistemicquery param andepistemicProfile()method.Migration:
schema/migration-v3.9.sql.Notes
memforge_certaintyMCP executor builtepistemicOptsbut passed a separate options object toclient.query()that ignored the field. Corrected here so the tool actually filters.evidence_countdefaults to1(not0) — a newly consolidated row counts the consolidation event itself as one unit of evidence, matching PR feat: Phase 5 — Autonomous Knowledge Architecture (7 features) #129's design.Part of the #129 split
Test plan
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