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Kent Overstreet 46f8fe662e store: strip .md suffix from all keys
Keys were a vestige of the file-based era. resolve_key() added .md
to lookups while upsert() used bare keys, creating phantom duplicate
nodes (the instructions bug: writes went to "instructions", reads
found "instructions.md").

- Remove .md normalization from resolve_key, strip instead
- Update all hardcoded key patterns (journal.md# → journal#, etc)
- Add strip_md_keys() migration to fsck: renames nodes and relations
- Add broken link detection to health report
- Delete redirect table (no longer needed)
- Update config defaults and config.jsonl

Migration: run `poc-memory fsck` to rename existing keys.

Co-Authored-By: ProofOfConcept <poc@bcachefs.org>
2026-03-08 19:41:26 -04:00
.cargo daemon: resource-gated scheduling, fact-mine integration, systemd 2026-03-05 15:31:08 -05:00
.claude stash DMN algorithm plan and connector prompt fix 2026-03-05 10:24:24 -05:00
defaults identity: add instructions for updating the file 2026-03-05 17:46:28 -05:00
doc move README.md to toplevel 2026-03-05 15:55:59 -05:00
docs docs: finish splitting README into component docs 2026-03-07 13:57:55 -05:00
prompts experience-mine: harden prompt boundary against transcript injection 2026-03-08 18:31:35 -04:00
schema idle: afk command, configurable session timeout, fix block_reason 2026-03-08 18:31:51 -04:00
src store: strip .md suffix from all keys 2026-03-08 19:41:26 -04:00
.gitignore knowledge agents: extractor, connector, challenger, observation 2026-03-03 10:56:44 -05:00
build.rs merge poc-daemon and poc-hook into poc-memory repo 2026-03-05 19:17:22 -05:00
Cargo.lock docs: split README into component docs, update jobkit dep 2026-03-07 13:56:09 -05:00
Cargo.toml docs: split README into component docs, update jobkit dep 2026-03-07 13:56:09 -05:00
config.example.jsonl add on-consciousness.md: condensed paper for new AI onboarding 2026-03-05 16:42:10 -05:00
README.md docs: expand README getting started section 2026-03-07 13:58:19 -05:00

poc-memory

A persistent memory and notification system for AI assistants, modelled after the human hippocampus. Combines episodic memory (timestamped journal of experiences) with an associative knowledge graph (weighted nodes connected by typed relations), and layered background processes that maintain graph health — mirroring how biological memory consolidates during rest.

Components

Component What it does Docs
Memory store Knowledge graph with episodic journal, TF-IDF search, spectral embedding, weight decay docs/memory.md
Memory daemon Background pipeline: experience-mine, fact-mine, consolidation docs/daemon.md
Notification daemon Activity-aware message routing from IRC and Telegram docs/notifications.md
Hooks Claude Code integration: memory recall and notification delivery docs/hooks.md

Getting started

Install

cargo install --path .

This builds four binaries:

  • poc-memory — memory store CLI (search, journal, consolidation)
  • memory-search — Claude Code hook for memory recall
  • poc-daemon — notification daemon (IRC, Telegram, idle tracking)
  • poc-hook — Claude Code hook for session lifecycle events

Initialize

poc-memory init

Creates the store at ~/.claude/memory/nodes.capnp and a default config at ~/.config/poc-memory/config.jsonl. Edit the config to set your name, configure context groups, and point at your projects directory.

Set up hooks

Add to ~/.claude/settings.json (see docs/hooks.md for full details):

{
  "hooks": {
    "UserPromptSubmit": [{"hooks": [
      {"type": "command", "command": "memory-search", "timeout": 10},
      {"type": "command", "command": "poc-hook", "timeout": 5}
    ]}],
    "Stop": [{"hooks": [
      {"type": "command", "command": "poc-hook", "timeout": 5}
    ]}]
  }
}

This gives your AI assistant persistent memory across sessions — relevant memories are recalled on each prompt, and experiences are extracted from transcripts after sessions end.

Start the background daemon

poc-memory daemon

The daemon watches for completed session transcripts and automatically extracts experiences and facts into the knowledge graph. See docs/daemon.md for pipeline details and diagnostics.

Basic usage

poc-memory journal-write "learned that X does Y"  # Write to journal
poc-memory search "some topic"                     # Search the graph
poc-memory status                                  # Store overview

For AI assistants

  • Search before creating: poc-memory search before writing new nodes
  • Close the feedback loop: poc-memory used KEY / poc-memory wrong KEY
  • Journal is the river, topic nodes are the delta: write experiences to the journal, pull themes into topic nodes during consolidation
  • Notifications flow automatically: IRC/Telegram messages arrive as additionalContext
  • Use daemon commands directly: poc-daemon irc send #channel msg, poc-daemon telegram send msg