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feat: Phase 5 — Autonomous Knowledge Architecture (7 features)#129

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salishforge wants to merge 2 commits into
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claude/codebase-cleanup-ycBzu
Open

feat: Phase 5 — Autonomous Knowledge Architecture (7 features) #129
salishforge wants to merge 2 commits into
main from
claude/codebase-cleanup-ycBzu

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@salishforge salishforge commented May 8, 2026

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Phase 5: Autonomous Knowledge Architecture

7 features that push MemForge beyond any competitor — from remembering to understanding.

New capabilities

# Feature Innovation New tools
1 Epistemic Confidence Model Calibrated uncertainty (established/provisional/contested/inferred) memforge_certainty
2 Explainable Memory Ops Every retrieval returns WHY via ExplanationFactor[] memforge_explain
3 Causal Memory Graph Inferred cause→effect chains, predictive queries memforge_causal_chain, memforge_predict
4 Hierarchical Abstraction Auto-extract principles from meta-reflections memforge_principles, memforge_mental_models
5 Adaptive Sleep Intelligence Per-phase analytics, auto-skip zero-change phases
6 Sentiment Tagging Urgency/sentiment/session_type on all memories
7 Transfer Learning Bootstrap new agents from experienced ones memforge_bootstrap

New sleep cycle phases

  • Phase 5.11: Principle Extraction (LLM extracts cross-cutting principles from meta-reflections)
  • Phase 5.12: Epistemic Promotion (auto-promote provisional→established with corroboration)
  • Phase 6.1: Causal Inference (mine temporal sequences for cause→effect patterns)

New REST endpoints

  • GET /memory/:id/epistemic — epistemic profile
  • GET /memory/:id/causal — causal chain traversal
  • POST /memory/:id/predict — predictive query
  • GET /memory/:id/principles — learned principles
  • GET /memory/:id/abstractions — all abstraction levels
  • POST /memory/:id/bootstrap — transfer learning

Stats

  • 1,268 lines added across 7 files
  • 7 new MCP tools (total: 54)
  • 6 new REST endpoints
  • 3 new sleep cycle phases
  • Schema migration: migration-v3.8.sql

Test plan

  • tsc --noEmit — 0 errors
  • Integration tests (need DB with v3.8 migration applied)
  • New feature-specific tests

https://claude.ai/code/session_0116EhmLb79eeBTN8P4wwFC1

claude added 2 commits May 8, 2026 08:47
1. Epistemic Confidence Model — calibrated uncertainty (established/
 provisional/contested/inferred) with evidence counting, auto-promotion
 via sleep Phase 5.12, and query-time epistemic filtering
2. Explainable Memory Operations — every retrieval returns WHY via
 ExplanationFactor[] (rank score, epistemic status, search mode,
 temporal decay). New memforge_explain tool for per-memory state audit
3. Causal Memory Graph — inferred cause→effect chains from temporal
 patterns via sleep Phase 6.1, recursive CTE traversal, and
 memforge_predict tool for "what typically follows X?"
4. Hierarchical Abstraction Engine — auto-extract principles from
 meta-reflections via sleep Phase 5.11, memforge_principles and
 memforge_mental_models tools
5. Adaptive Sleep Intelligence — per-phase analytics tracking,
 auto-skip phases with 3 consecutive zero-change cycles
6. Memory Sentiment Tagging — keyword-inferred urgency/sentiment/
 session_type context signals on hot and warm tiers
7. Cross-Agent Transfer Learning — memforge_bootstrap copies
 established knowledge between agents with confidence discounting
 and provenance tracking
Schema: migration-v3.8.sql (epistemic columns, causal_edges,
abstractions, sleep_phase_analytics, context_signals)
New MCP tools: memforge_certainty, memforge_explain, memforge_causal_chain,
memforge_predict, memforge_principles, memforge_mental_models,
memforge_bootstrap
New REST endpoints: /epistemic, /causal, /predict, /principles,
/abstractions, /bootstrap
https://claude.ai/code/session_0116EhmLb79eeBTN8P4wwFC1 
...orts
- Add epistemic_status, evidence_count, context_signals columns to
 canonical hot_tier and warm_tier definitions
- Add causal_edges, abstractions, sleep_phase_analytics tables
- Add RLS policies for new tables
- Remove unused EpistemicStatus, EpistemicFilter, PhaseAnalytics imports
Fixes CI lint errors and integration test failures from missing columns.
https://claude.ai/code/session_0116EhmLb79eeBTN8P4wwFC1 
salishforge added a commit that referenced this pull request May 21, 2026
- Memory Sentiment Tagging (F6): infer urgency/sentiment/session_type
 from content at add and consolidation time. New context_signals
 JSONB column on hot_tier and warm_tier. During consolidation,
 signals from all contributing hot rows are merged: urgency = max,
 sentiment = majority, session_type = majority. query() returns
 context_signals on each QueryResult. New types UrgencyLevel,
 SentimentTag, SessionType, ContextSignals.
- Adaptive Sleep Intelligence (F5): per-phase telemetry in new
 sleep_phase_analytics table. Two new methods on SleepCycleEngine:
 recordPhaseAnalytics() and shouldSkipPhase() (skips phases whose
 last 3 runs had zero changes_made). Index + RLS policy included.
Migration: schema/migration-v3.8.sql (idempotent ADD COLUMN IF NOT EXISTS)
Tests: 29 sentiment + 18 adaptive-sleep (unit/integration/migration)
Split from #129 (PR-A).
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
salishforge added a commit that referenced this pull request May 21, 2026
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>
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