The memory and workspace layer for AI coding agents.

Bounded and self-consolidating

Duplicate entities merge across modules and a global importance cap evicts the least-connected, so the always-on cost stays flat while accuracy rises. The memory gets leaner and sharper the more you build, not heavier.

Nothing shrinks without a way back

Pin an entity and the cap can never evict it. Fence a region of CLAUDE.md and AI compression never even sends it to the model. Prune names what it will drop before it drops it. Every replacement is snapshotted and restorable, and restoring is itself snapshotted.

Temporal facts

When you migrate Flask to FastAPI the old fact is invalidated with a timestamp rather than deleted — kept as history, never injected. Memory tracks what is true now and what changed, instead of drifting stale.

It learns from every session

Durable lessons — error to fix pairs, decisions, preferences — are distilled from transcripts, reviewed, injected when relevant and decayed when unused. Conventions that recur across your repos are promoted to your user-level CLAUDE.md, so a rule learned once is remembered everywhere.

Local, deterministic retrieval

Four rankers combined by Reciprocal Rank Fusion, which uses each ranker’s position rather than its score, so nothing needs calibrating. No embeddings, under half a second on 500 entities. The honest limit: this is lexical retrieval — a query sharing no vocabulary with the stored summary will miss.

Graph memory is inspired by cognee and retrieval budgeting by Aider’s repo-map; both were reimplemented from scratch in pure stdlib.

Context weight audit

One screen estimating the tokens auto-loaded on every turn for this project: CLAUDE.md broken into its blocks, the global CLAUDE.md, rules files marked lazy when they are glob-scoped, the system prompt, SessionStart hook injections and MCP servers — with a running always-on total and inline warnings.

Prune and compress

The session-topics log is capped to the most recent entries and rebuilt in place. AI compression rewrites the hand-written part into a lean lookup-table style, shows a before-and-after token count and a diff to approve, and preserves the machine-maintained blocks verbatim.

Deny heavy reads

Scans the project and writes permissions.deny rules for node_modules, dist and lockfiles into the project settings, so a stray read cannot pull thousands of tokens of generated content into context.

Cheaper models for the grunt work

archeus’s own internal calls default to a cheap economy model. Plan → Execute runs the expensive model once for the plan and a cheap — or, through OmniRoute, a free — one for execution.

Measured, not asserted

Rule files were being loaded on every turn because they carried Cursor’s frontmatter key rather than Claude Code’s. Fixing it took this repository from 22,238 always-on tokens to 18,363 — 3,875 off every single turn.