Hinweis: Der zugehörige Subagent-Transcript lieferte keine Assistant-Antwort (nur User-Prompt). Dieser Report wurde direkt aus
~/.hermes/, Cursor/Codex-Skills und den fertigen Schwester-Reports rekonstruiert (Stand: Juli 2026).
Memory & Knowledge Architecture
Three-tier memory model
Samuel's stack deliberately splits memory by purpose instead of one vector DB:
| Tier | Mechanism | What it stores | Authority |
|---|---|---|---|
| A. Course / project files | ~/TH-Mannheim/, project repos, HAI markdown |
Durable learning & shipping truth | Highest for uni + code |
| B. Knowledge Graph MCP | LightRAG-style stores via knowledge-graph MCP |
Session ingestion, thoughts, cross-project links | Exploratory / recall |
| C. Hermes profile memory | memory: in config + memories/, global_memories/ |
Short user profile snippets, nudges | Low caps (5k/2.5k chars) |
Plus intake register (voice → structured records) and Plaud/hai-intake MCP for packet-oriented context.
Hermes built-in memory (config)
memory_enabled: true
user_profile_enabled: true
memory_char_limit: 5000
user_char_limit: 2500
Design signal: Hermes memory is a lightweight personalization layer, not the cognitive substrate. Heavy context is expected from files + MCP.
global_memories/ holds shared USER.md / MEMORY.md style manifests — copy-only backups exist, suggesting careful migration history.
Knowledge Graph MCP (Cursor)
Registered in ~/.cursor/mcp.json as knowledge-graph. Used when Samuel/context is unclear — query before guessing (per cursor workflow rule). Ingestion paths include agent sessions, folders, prompts DB (per kg skill docs).
Strength: cross-session associative recall without stuffing prompts.
Risk: graph quality depends on ingestion hygiene; stale nodes if not curated.
Intake & voice memory
intake-router-hermes maintains a routing register with structured fields (topics, projects, urgency, confidence). get_context_package style tools bridge Plaud transcripts to agents.
This is event-sourced personal memory — optimized for "what did I say about project X?" rather than embedding search alone.
Uni learning rule (critical)
From AGENT_DIRECTORY.md:
Source of Truth ist
~/TH-Mannheim/, nicht Profilmemory.
Fach agents must not substitute chat memory for coursework. This prevents confident hallucination of lecture content — a common failure mode in student agent setups.
ADHS profile as meta-memory
ADHS_LEARNING_PROFILE.md acts as procedural memory — how to teach Samuel — loaded fresh each message. It is not factual storage but strongly shapes retrieval prompts and session shape.
Gaps vs. GBrain / OneBrain indie pattern
Indie "second brain" setups often run overnight enrichment (66 cron jobs in GBrain lore). Samuel has cron/kanban infrastructure but less autonomous memory consolidation while asleep.
Strengths
- Clear authority hierarchy (course folders > register > KG > profile memory).
- MCP makes memory tool-addressable from Cursor and Hermes.
- Intake pipeline captures pre-artifact thoughts that would otherwise die in voice notes.
Weaknesses
- Synchronization — same fact may exist in KG, register, and a project README with no single merge.
- No unified query UI — Samuel must know which tier to query.
- Profile memory caps can truncate nuance unless flushed to files (depends on discipline).
- Checkpointing disabled in HAI flows — memory of in-progress reasoning lives in chat logs, not resumable state machines.
Recommendations
- Nightly register → KG promotion job for high-confidence intake rows only.
- Tag KG nodes with authority level metadata (course / project / thought).
- Weekly memory audit skill: find contradictions between USER.md and project STATE files.
- Borrow completion + consolidation cron from indie setups — one job, not 66.