mind

Local, deterministic memory for coding agents.

What It Is

mind stores durable project facts in a weighted concept graph, recalls them through lexical ranking plus spreading activation, tracks where every fact came from, ages unused salience, and consolidates recurring themes through a deterministic dream cycle.

The default runtime is:

• local and plain-text;
• Python standard-library only;
• deterministic and offline;
• agent-neutral;
• distributed as one auditable mind.py file.

The development source is split by domain under src/mind/. A deterministic builder reconstructs the single-file artifact byte-for-byte.

Verified Status

• Development version: 7.0.1.dev0 (preview).
• Stable release: 7.0.0; pinned mind.py SHA-256 ae2fc389b3b09c93cb432ab55b71063d98b400da6b18d6bc178322bc8f3fcf69.
• Discovered tests: 382.
• Distribution: 10 source-domain fragments build one deterministic file; current artifact SHA-256 182322c812686d5885423f90943a66898236ec04a1ed84ce5b52feb9a4364aee.
• CI matrix: 9 operating-system/Python cells.
• Command line: 30 commands; protocol server: 17 tools.

7.0.1.dev0 is the current development preview. The production-ready release is 7.0.0, which contains the lifecycle, protocol-server, typed-memory, privacy, automatic-capture, and modular-source features documented below.

Install

Stable release

curl -fsSLO https://raw.githubusercontent.com/Da7-Tech/mind/v7.0.0/mind.py
python3 -c "import hashlib; p=open('mind.py','rb').read(); assert hashlib.sha256(p).hexdigest() == 'ae2fc389b3b09c93cb432ab55b71063d98b400da6b18d6bc178322bc8f3fcf69'"
python3 mind.py init

Development source

git clone https://github.com/Da7-Tech/mind.git
cd mind
python3 tools/build_single.py --check
python3 mind.py init

On stock Windows, exported commands use py -3 mind.py. A Windows CI field test converts the artifact to CRLF, runs the exported invocation verbatim, and checks the resulting project.

Memory Model

Layer	Storage	Role
Working memory	.mind/ACTIVE.md	bounded hot facts and operating contract
Hippocampus	.mind/graph.json	typed facts, validity, weights, relations
Provenance	.mind/journal.jsonl plus segments	append-only operation history
Cortex	.mind/cortex/*.md	recurring themes with owned guard blocks
Dreams	.mind/dreams/*.md	human-readable maintenance receipts
Scheduler	.mind/scheduler.json	bounded lease and pending-maintenance state
Pending queue	.mind/pending.json	quarantined automatic captures

Facts can be semantic, episodic, procedural, or decisions. They also carry scope, authority, source trust, sensitivity, expiration, pinning, and optional entity/attr slots for contradiction detection.

Auto-First Operation

mind init exports a guard-marked standing-order block into AGENTS.md, CLAUDE.md, and GEMINI.md. Existing content outside the generated block is preserved byte-for-byte. Existing Cursor, Windsurf, Cline, and Roo rule files are adopted when present.

Agents use:

python3 mind.py capture "durable project fact"

Automatic capture:

• accepts stable project decisions, conventions, and environment facts;
• rejects credential and personal-identity patterns;
• rejects transient task state;
• quarantines untrusted material for review;
• infers conservative memory types and common contradiction slots;
• never copies project memory into the user-global tier.

Dream scheduling is independent from the telemetry log. A bounded scheduler uses a lease, pending count, and recovery rules. Oversized telemetry resets safely without disabling future maintenance.

Host integrations can consume machine-readable recipes:

python3 mind.py integrations --json
python3 mind.py context --json

The recipes cover session start, durable capture, pre-compaction batch flush, session end, an optional scheduled backstop, and the protocol server.

Command Surface

init
--help
--version [--verbose]
remember "text"
remember --user "text"
remember --json
remember --batch
capture "text" [--trust LEVEL]
pending
approve ID
reject ID
context [--json]
suggest-user [--json]
integrations [--json]
recall "question" [--at DATE] [--explain]
confirm ID [...]
correct "old hint" "new fact"
link "a" "b" [relation]
forget ID [--reason TEXT]
unlink A B
redact ID --reason TEXT
purge ID|--match TEXT --all-traces [--confirm]
why ID
entity "term"
dream [--dry-run]
backup [label]
checkpoint [label]
restore NAME [--confirm]
compact [--dry-run] [--keep-journal-days N]
merge BASE OURS THEIRS [--output PATH] [--graph-out PATH]
doctor [--bench] [--json]
growth [--days N] [--json]
export
status
mcp

Use recall -- "-query beginning with a dash" for a dash-leading query.

Recall And Explainability

Offline recall combines:

1. script-aware tokenization and normalization;
2. inverse-document-frequency direct matching;
3. related-term expansion;
4. bounded spreading activation over weighted relations;
5. reciprocal-rank fusion;
6. optional whole-ranking semantic reranking.

recall --explain prints direct, spread, fused, semantic, and final scores, plus backend identity, process calls, latency, and fallback reason. Recall is a pure read; useful hits change durability only after explicit confirm.

Directional relations such as depends-on, owned-by, and deployed-to store truthful reverse labels while retaining bidirectional traversal.

Optional Semantic Backends

The default remains offline. Two explicit optional protocols exist:

• MIND_EMBED_CMD: one versioned batch process per ranking;
• MIND_EMBED_SERVER: a persistent length-framed process with handshake, model revision, and dimension identity.

Both paths have bounded output, vector dimension, cache bytes, and total ranking deadlines. A partial failure falls back the entire ranking to the offline metric; similarity spaces are never mixed.

Reference server:

export MIND_EMBED_SERVER='python3 contrib/concept_embed_server.py'
python3 mind.py recall "where are backup copies kept" --explain

The process receives the query and candidate memory text. Only configure a program you trust. The tool does not enforce that program's network isolation.

Agent Protocol Server

python3 mind.py mcp

The same file serves newline-delimited JSON-RPC over standard input/output. It supports initialization, ping, tool listing/calls, cancellation notifications, clean EOF shutdown, and seventeen memory, diagnostic, and privacy tools. Standard output contains protocol JSON only.

Minimal lifecycle:

initialize
notifications/initialized
tools/list
tools/call
notifications/cancelled

Storage Lifecycle

status separates current journal bytes from segment count and segment bytes. compact rotates an oversized active archive, segments a current journal when it exceeds budget or is wholly older than the requested retention horizon, and collects stale temporary files.

Backups are plain files with a SHA-256 manifest:

python3 mind.py backup before-upgrade
python3 mind.py restore BACKUP_NAME
python3 mind.py restore BACKUP_NAME --confirm

A confirmed restore creates a pre-restore checkpoint first. Privacy rewrites also refresh backup manifests so a remediated backup remains verifiable. Restore writes an exact file plan, removes later managed files, and resumes an interrupted plan before normal memory loading.

Privacy Lifecycle

• forget removes a fact from retrieval but keeps an auditable tombstone.
• unlink removes a relation without deleting its endpoints.
• redact replaces payloads with a digest and reason across managed stores.
• purge inventories first; --confirm irreversibly removes payload and node identifiers from graph, journals, archives, dreams, cortex, exports, queues, receipts, and backups.

Redaction and purge use a crash-resumable outbox. Exact-byte tests search every managed artifact after completion. Secrets should still never be stored: remediation is a last resort, not a secret manager.

Git-Mergeable Memory

Journal format v2 adds UTC epoch-nanosecond time and stable event IDs. The three-way merge command deduplicates suffix events, orders them deterministically, and can replay the merged journal into a graph:

python3 mind.py merge BASE OURS THEIRS --output MERGED --graph-out GRAPH

Example merge driver:

[merge "mind-journal"]
    name = deterministic mind journal merge
    driver = python3 mind.py merge %O %A %B --output %A

.mind/journal.jsonl merge=mind-journal

On Windows, replace python3 with py -3.

Diagnostics And Felt Growth

python3 mind.py doctor --bench
python3 mind.py growth --days 30
python3 mind.py suggest-user

doctor checks storage boundaries, recovery outboxes, scheduler leases, duplicate export guards, BOM/CRLF handling, stale temporary files, backend configuration, and clock anomalies. Its optional personal benchmark appends a local recall history.

growth derives learned, confirmed, corrected, forgotten, dreamed, promoted, and conflict counts from journal and dream truth. The latest bounded consolidation receipt is visible in every generated ACTIVE.md.

Reproducible Evidence

Every public result is JSON tied to an immutable input, source identity, backend identity, and exact command.

Result	Current evidence	Raw report
BM25 baseline	0.660 / 0.920 / 0.560	longmemeval-bm25-v7-dev.json
mind offline	0.500 / 0.840 / 0.580	longmemeval-offline-v7-dev.json
mind with concept sidecar	0.560 / 0.840 / 0.520	longmemeval-concept-v7-dev.json
Paraphrase traps	offline 0/20; sidecar 20/20	paraphrase-v7-dev.json
10,000-fact bulk ingest	one commit; conservative 91.0x speedup	bulk-v7-dev.json
Auto-first horizon	30 sessions and 1825 simulated days	autonomy-five-year-v7-dev.json
Single-file mutations	43/120 killed (35.8%); 77 survived	mutation-mind-v7-dev.json
LongMemEval-harness mutations	35/120 killed (29.2%); 85 survived	mutation-longmemeval-v7-dev.json

On this subset, BM25 leads both evidence metrics. This benchmark does not measure graph traversal, temporal validity, contradiction handling, or lifecycle operations, so it does not establish overall product superiority.

LongMemEval values are evidence@1 / evidence@5 / answer-string@5.

Raw files live under bench/results/. The LongMemEval input is pinned by revision and SHA-256 in bench/manifests/longmemeval.json.

LongMemEval memory records include metadata prefixes such as date, question ID, session ID, and role. These prefixes improve provenance and isolation but also add query-independent tokens; evidence metrics therefore use exact node labels, and answer-string metrics are reported separately.

Mutation analysis performs a green product-suite baseline preflight, stages every product-test dependency, mutates modular source and artifact consistently, preserves bounded diagnostics, and distinguishes killed, survived, timed out, compile error, and infrastructure error. The three self-referential public-evidence tests run after report generation because they validate the completed report itself; every report records this exclusion and the exact baseline test count.

Boundaries And Non-Goals

• Maximum graph: 10,000 nodes, 100,000 directional edges, 50 MB.
• Maximum fact/query: 10,000 characters.
• Active archive rotates at 8 MB.
• Signals reset at 5 MB; scheduling survives independently.
• The default is project memory, not document-scale RAG.
• Dreaming is consolidation, not rollback.
• A pruned fact is archived; a pruned edge is not restorable automatically.
• Automatic capture depends on a host following the exported contract or calling the protocol/hooks. No tool can force a host that ignores both.

Development

Environment

Variable	Purpose
MIND_AUTO_DREAM	Set to 0, false, or no to disable write-triggered maintenance.
MIND_BY	Bounded provenance actor supplied by a host integration.
MIND_SESSION	Bounded provenance session supplied by a host integration.
MIND_USER_HOME	Explicit user-tier directory; defaults to ~/.mind.
MIND_EMBED_CMD	Optional one-process batch semantic command.
MIND_EMBED_SERVER	Optional persistent framed semantic server.
MIND_EMBED_TIMEOUT	Per-operation semantic timeout.
MIND_EMBED_BUDGET	Total semantic ranking deadline.
MIND_LOCK_TIMEOUT_SECONDS	Cross-process graph-lock deadline.
MIND_DEBUG	Print tracebacks for command failures.

python3 tools/build_single.py --check
python3 tools/claims.py check
python3 -m unittest discover -s tests -v
python3 bench/bench.py
python3 bench/multilang.py
python3 bench/discrim.py
python3 bench/slots.py
python3 bench/soak.py
python3 bench/fuzz.py --quick
python3 bench/autonomy.py --quick

Release-only gates also run the full five-year autonomy horizon, immutable LongMemEval subset, both mutation targets, privacy scan, and all nine CI cells. See the V7 verification record for the three-method gate, raw evidence, limitations, and remote completion requirements.

Security

Read SECURITY.md before enabling an external semantic backend or storing sensitive project material. The default kernel does not use the network or child processes. Optional semantic modes execute a trusted local program and pass memory text across that process boundary.

MIT licensed.