OptMem

Permanent memory for AI agents. Nothing is ever deleted, and what the agent reads at wake is always the same size.

Install

curl -fsSL https://raw.githubusercontent.com/VictorTaelin/OptMem/main/install.sh | sh

It prints a ## Memory block. Paste that at the top of your agent's AGENTS.md (or CLAUDE.md), and you are done: no daemon, no database, no embeddings, no plugin. Run the same line again to update.

Commands

memo wake	read the memory — the first command of every session
memo note "..."	record one memory: one line, up to 280 chars
memo sleep	answer the merges that came due
memo recall <regex>	search every memory ever recorded, word for word
memo forget <lo>-<hi>	drop a bad summary; the next sleep rebuilds it

Merges arrive one at a time, in the output of note. Nothing ever runs in the background.

Files

~/.optmem/
  memo          the tool (Python 3, no dependencies)
  blocks.py     which memories to read, and which to merge
  memory/
    LOG.txt     every memory, one per line, append-only, never edited
    TREE/       the summaries: a cache, rebuildable from the log alone
    config      the sizes, all commented out

WAKE_LINES is the only size worth touching: how many lines wake prints (208 ≈ 16k tokens). It is a reading budget, not a storage budget — change it whenever, in either direction, and nothing is recomputed.

Records are fixed width, so position is identity and every lookup is one seek. At a million memories (607 MB), wake takes 0.03s.

Set $MEMORY_DIR to keep memory/ elsewhere — a synced folder, a git repo.

Limitations

Recency is the only axis: an old memory fades however important it was, and the one defence is rehearsal — note it again and it is recent again. recall is regex, not semantic search. Summaries are written by the agent out of other summaries, so a bad one spreads upward until you forget it. And a wake costs ~16k tokens, which is deliberate but not free. If you need a fact database, use a wiki — this is for who the agent is.