Metadata-Version: 2.4
Name: remaind
Version: 0.9.7
Summary: Local-first memory and context continuity for AI agents working beyond one context window.
Project-URL: Homepage, https://remaind.draftlabs.org
Project-URL: Documentation, https://remaind.draftlabs.org/integrate
Author: Draft Labs
License: Proprietary
License-File: LICENSE
Keywords: agents,compaction,context,handover,ledger
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: Other/Proprietary License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Topic :: Software Development :: Libraries
Requires-Python: >=3.11
Requires-Dist: jsonschema<5,>=4.18
Requires-Dist: pyyaml<7,>=6.0
Provides-Extra: dev
Requires-Dist: mypy>=1.10; extra == 'dev'
Requires-Dist: pytest-cov>=5.0; extra == 'dev'
Requires-Dist: pytest>=8.0; extra == 'dev'
Requires-Dist: ruff>=0.6; extra == 'dev'
Requires-Dist: types-jsonschema>=4.18; extra == 'dev'
Requires-Dist: types-pyyaml>=6.0; extra == 'dev'
Description-Content-Type: text/markdown

# Remaind

[![pypi](https://img.shields.io/pypi/v/remaind)](https://pypi.org/project/remaind/)
[![python](https://img.shields.io/badge/python-3.11%2B-blue)](#)
[![license](https://img.shields.io/badge/license-proprietary-lightgrey.svg)](LICENSE)

**Local-first memory and context continuity for AI agents working beyond one context window.**

Remaind is a local-first context ledger, compaction pipeline, and resume
substrate for AI agents, local models, OpenAI-compatible API models, coding
agents, and automation workflows. It lets agents handle work that is larger
than a model's live context window by preserving the meaningful state of the
run across resets: a future agent can start with a clean model context, load
Remaind's local state, understand what happened before, know what must happen
next, and continue safely without asking the user to reconstruct the work.

Remaind is not a wiki — it is a **machine-readable and human-readable
continuity layer**: raw event ledger, structured state, compact handover,
searchable memory, structured validation, safe rollback, and a mechanical
resume gate.

Remaind also treats retrieved memory as evidence, not instructions. The resume
gate uses mechanical, defense-in-depth heuristics to flag known hostile
instruction shapes before a fresh model sees retrieved memories or raw excerpts,
and the compaction validator rejects poisoned local model output before it can
become durable memory. These checks improve hygiene around untrusted content;
they are not a standalone security boundary.

New events are also hash-chained in their metadata. `remaind validate` verifies
that chain and reports tampering when a chained event edit, deletion, or reorder
breaks continuity. Resume packets label retrieved events and memories with
mechanical trust hints such as `user`, `verified_tool`, `assistant`, or
`source_linked_memory`.

## Install

```sh
python3 -m pip install --upgrade remaind
remaind --version
remaind launch
```

Requires Python ≥ 3.11. The install gives you the `remaind` terminal command,
local memory/state storage, context packets, plan reconciliation, rollback,
monitoring, large-document tools, and model-agnostic launch/run flows.

Remaind does not install Python, local model runtimes, model files, or API
credentials. For model-generated answers, choose one of these at launch:

- a local Ollama model
- a local OpenAI-compatible server such as llama.cpp, vLLM, or LM Studio
- an API-backed OpenAI-compatible endpoint, including Qwen-style services
- packet-only / no-model workflows when you only need memory, context
  inspection, or recovery artifacts

If `python3` is missing, install Python 3.11+ first, then run the install
command above.

## Sovereign Memory Starter Kit

Remaind now ships a portable product kit for users who want a complete local
agent memory setup rather than only the Python library:

```text
starter-kits/sovereign-memory-starter/
```

The starter kit adds:

- one-command bootstrap/setup, readiness checks, and launch
- managed Python bootstrap through local, checksum-verified `uv` when Python 3.11+ is missing
- model profiles for Qwen, DeepSeek, DeepSeek v4 Flash, GLM, Minimax-style, Llama, and custom local models
- Ollama and OpenAI-compatible local compaction/chat, including llama.cpp server
- Qwen Code and built-in console adapters
- a synthetic continuity proof (`make proof`) that verifies fresh-process retrieval
- a beyond-context benchmark (`make bench`) for distant contradiction,
  revocation pressure, source-link, and adversarial checks
- a direct large-prompt runner (`remaind run FILE "TASK"`) that builds a
  compact evidence packet before calling the configured local model
- a model battle-test harness (`make model-test`) for deterministic Remaind
  retrieval checks plus optional local model matrix testing
- privacy-safe sharing: each user gets their own `.context/` ledger

Quick start from the repo:

```sh
cd starter-kits/sovereign-memory-starter
./bootstrap.sh --profile qwen-large --agent qwen-code
remaind
```

Console-only local proof:

```sh
cd starter-kits/sovereign-memory-starter
./bootstrap.sh --agent console --profile llama
make proof
```

Build the distributable zip:

```sh
scripts/build-sovereign-memory-starter.sh
```

This writes a release archive under `dist/`.

See the full product guide in
[docs/sovereign-memory-starter.md](docs/sovereign-memory-starter.md).
For the day-one workflow of starting a product and later continuing from
memory without manual packet management, see
[docs/zero-to-continuation.md](docs/zero-to-continuation.md).

## Quick start

```sh
# Install or upgrade from PyPI.
python3 -m pip install --upgrade remaind

# Check the installed version.
remaind --version

# Run the 5-minute deterministic proof path.
remaind proof

# Start the guided workflow after the proof passes.
remaind launch

# Or bootstrap a .context/ in the current directory manually.
remaind init

# Inspect what's there.
remaind validate
remaind status
remaind doctor

# One front-door startup: product/workspace lookup first, model/runtime
# selection next, then ask, paste, file, resume, handover, or empty mode.
remaind launch

# After work happens (events appended by your agent harness),
# compact when token band climbs.
remaind compact

# Build a resume packet for a fresh agent run.
remaind resume --next-tool deploy_prod

# Register a huge local Markdown/text file, then retrieve exact evidence
# by search or line range without loading the whole file into the prompt.
remaind large-doc ingest /path/to/large-archive.md
remaind large-doc search /path/to/large-archive.md "final synthesis phrase" --verify
remaind large-doc slice /path/to/large-archive.md --start 33557 --end 33565 --verify

# Or execute a task against a huge local prompt/document in one command.
remaind run /path/to/huge-prompt.md "solve this task"

# Roll back if something went wrong.
remaind rollback --to 2026-05-14T03:54:33Z
```

## Use it as a library

`import remaind` is the stable public API — `remaind.__all__` is the whole
surface. The underscore-prefixed modules are internal.

```python
import remaind

base = "./my-agent-run"
remaind.init(base)

state = remaind.status(base)
writer = remaind.EventWriter.open(base)
writer.append(remaind.EventInput(
    type="user_message", actor="user", summary="Asked to refactor auth",
    session_id=state["session_id"], task_id=state["task_id"],
    content="Please refactor src/auth/...", importance=3,
))

if remaind.compaction_status(base).compaction_needed:
    remaind.compact(base)   # uses your local model if one is running

packet = remaind.resume(base).packet   # inject packet.content into a fresh context
```

**Full walkthrough — the agent-loop integration, how compaction uses your
local model, the resume-injection pattern, and an exception reference — is
in [docs/integration.md](docs/integration.md).**

Adversarial memory behavior is documented in
[docs/adversarial-hardening.md](docs/adversarial-hardening.md).
Executable product proofs are documented in
[docs/benchmarks.md](docs/benchmarks.md).
The fastest public trust path is `remaind proof`: it creates isolated local
proof workspaces, runs the project-continuity benchmark, runs the sovereign
beyond-context benchmark, and prints one PASS/FAIL report with the claims each
check proves. The proof contract is documented in
[docs/proofs/golden-proof-path.md](docs/proofs/golden-proof-path.md).
The finance policy-exception continuity walkthrough is in
[docs/proofs/finance-policy-exception-continuity.md](docs/proofs/finance-policy-exception-continuity.md).

## Large Local Documents

Agent terminals can read files that agent UI file-readers often refuse to load.
Remaind exposes that as a product feature through `remaind large-doc`.
For the guided terminal workflow, `remaind launch` activates memory, verifies
runtime readiness, and only then asks whether to ask a project question, paste
text, load a file, prepare a resume packet, or start empty:

```sh
remaind launch
remaind launch --project "Rutwais"
remaind launch --path ./my-project --input ask --task "status of Rutwais?"
remaind context inspect --project "Rutwais" "what is the current plan and next step?"
remaind launch --path ./my-project --input file --file /absolute/path/to/huge.md
cat /absolute/path/to/huge.md | remaind launch --path ./my-project --input paste --task "solve this task"
```

In an interactive terminal, `remaind launch` opens a session home first. Use the
Up/Down keys and Enter to choose `New session`, `Open by name or topic`,
`Continue last project`, one of the last 10 recent projects, the current folder,
or a manual path. New sessions get their own timestamped workspace folder by
default, so each product session can keep a dedicated `.context/`.

When you choose `Open by name or topic`, type something like `Rutwais` or
`local llm test`. Remaind builds a workspace-memory index from existing
`.context` folders, then searches folder names, paths, handover, state, recent
packets, and recent events. The lookup tolerates hyphens, close spellings, and
related topic phrases such as `merchant refunds`. Only strong matches open
automatically; weak or ambiguous matches are shown as selectable full paths. If
nothing matches, launch offers to create a new session named after what you
typed, browse existing projects, or try another name. Remaind remembers safe
project-name aliases, but ignores generic shell phrases such as `which remaind`
so Recent Projects stay readable.

`Activate memory and return to terminal` and `Prepare resume packet` are
memory-only flows and do not probe, load, or call a model. Model/runtime
selection is delayed until you choose a mode that needs generation, such as
asking Remaind memory, loading a file, pasting text, or updating handover. The
empty terminal path reports `Runtime: not selected for this mode`; that means
model selection was skipped for speed, not that DeepSeek or another configured
model is unavailable. The model picker lists detected local
Ollama/OpenAI-compatible models before the readiness check. If a selected model
fails its smoke test, launch lets you choose another detected model before
offering packet-only fallback. File mode lists registered large documents and
nearby Markdown/text/JSON-style files. Use the visible `Back` row to return to
the previous step without restarting.
Press `m` for a manual path when the path you need is not listed. The
continuation picker also includes `Update handover.md`; in terminal selectors,
`Ctrl+H` activates that handover update shortcut.

For the closest thing to always-on memory, install the daemon shell hook:

```sh
eval "$(remaind daemon shell-init --shell zsh)"
```

Or install it once:

```sh
remaind daemon install-shell-hook --shell zsh
```

The hook keeps the active-memory prompt hint and records privacy-safe work
signals after each command: sanitized command preview, exit code, rough
duration, current folder, git branch, and changed files. It never records
terminal output. Meaningful developer commands and failed developer commands
update the product status and product-plan reconciliation automatically, so
Remaind can recover the latest activity and map it back to the active plan even
if the terminal closes unexpectedly.
On zsh, the hook also routes plain-English questions typed at an active-memory
prompt through `remaind ask` before zsh treats them as shell commands. For
example, after opening a workspace, `is the repo cloned locally?` is converted
to a Remaind memory question instead of producing a shell glob error. The last
workspace opened through `remaind launch` becomes the active memory target for
these follow-up questions.

After choosing a workspace, the default path is normal terminal/LLM usage:
press Enter and choose `Activate memory and return to terminal` to activate
memory and return control without putting Remaind between you and the model. You
are back in your shell after this path; plain natural-language questions should
be asked through your normal LLM interface or with `remaind ask "your question"`.
Type memory-specific questions such as `what is the next step?`,
`latest progress and TODOs`, or `ask what did we finish last?` when you want
Remaind to build context and answer from memory. Type `prepare memory packet`,
`update handover`, `paste`, `file`, or a document path to route to those
explicit Remaind workflows. Generic LLM prompts typed at this point are saved as
lightweight launch notes and returned to the normal session instead of being
processed before the LLM.

On MOSAI/DeepSeek installs that include the profile switcher, launch also shows
a `DeepSeek mode` picker before model selection. Choose `Turbo - faster, 65k
context` for day-to-day speed or `Stable - larger, 131k context` when the task
needs the widest local context. The switch restarts the supervised DeepSeek
server, updates Remaind's packet/context settings, and then continues through
the normal readiness checks.

If you do not have a local LLM, choose
`Connect API model (OpenAI-compatible)` from the model picker. Remaind asks for
the service's `/v1` endpoint, accepts an optional bearer token for the current
launch only, lists the API models it can discover, and then runs the same
readiness check before any project question or large prompt is processed. The
API key is not written into `.context/`.

Ask Remaind memory mode runs your question against the current resume packet.
It is intentionally a memory-QA path, not the default chat path. If you choose
`Prepare resume packet only`, interactive launch offers to ask a question from
that packet before returning to the shell, so natural text like
`status of Rutwais?` is captured by Remaind instead of being interpreted as a
terminal command. Follow-up questions in the same launch carry the current
terminal conversation forward, so corrections like “the model is already
working” are treated as newer than stale packet failures. If you ask for recent
packets, launch includes the latest run packets and answer notes as evidence for
that question. More generally, memory questions now include a workspace packet
inventory so the model knows which prior packets and answer notes exist. Normal
questions include recent packet context; requests for `all packets` or
`full history` load every packet and answer note that fits the fixed
question-source budget and clearly list anything omitted.
For speed, launch answers operational checks such as “is Remaind active?” and
terminal-command inputs such as `gh repo clone ...` locally instead of sending
them through the model. Model-backed memory questions use a launch-specific
timeout cap, `REMAIND_LAUNCH_ASK_MODEL_TIMEOUT` (default `45` seconds), so a
slow or stalled local model cannot leave the interactive chat waiting for the
general model timeout.
The same context-engineering trace is now part of all model-facing context:
resume packets, `remaind run` retrieval-planner prompts and evidence packets,
handover compaction prompts, and deep-document compaction prompts all label
selected evidence by authority, freshness, and budget status before a model
sees it.
When your goal is to resume work, use normal language such as
`continue working on this project`, `what is the next step?`, or
`latest progress and TODOs`. Remaind treats that as a continuation request:
the LLM receives the resume packet plus budgeted packet-library context and is
asked to reconstruct the product scope, active plan, latest progress, blockers,
next TODOs, and the immediate implementation step before it answers.
On activation, Remaind also seeds a durable product-status record when one does
not exist yet. That seed is intentionally conservative: it says memory is
active, no product progress or blocker has been captured yet, and the next
answer should use the workspace plan, handover, and packet evidence to choose
the real next step. Remaind also writes
`.context/active/plan_reconciliation.md` and
`.context/active/plan_reconciliation.json`, which turn loaded plan/status files
plus saved activity into a plain-English map of completed, blocked,
in-progress, pending, and planned work. Continuation answers use that
reconciliation before old packets or old model answers.

For advanced local setups, each detected model is available in normal mode and
YOLO mode, for example `deepseek-v4-flash` and
`deepseek-v4-flash (YOLO / skips model test)`. That lets you choose the model
without typing or thinking about provider endpoints. The `Model not listed`
entry is only for unusual cases where a local model exists but does not appear
in discovery. The rest of readiness still runs, and the launch report labels
the model as unverified. The same path is available in scripts with:

```sh
remaind launch --runtime ollama --model any-local-model:latest --yolo-model
```

Paste mode is intentionally available after readiness. It captures pasted or
stdin text into `.context/artifacts/launch-pastes/` and routes that captured
file through the same large-prompt packet path, so a long terminal session can
start naturally without pushing raw text into the model before memory is active.

For the shortest one-shot workflow, `remaind run FILE "TASK"` combines
initialization, ingest, retrieval, packet writing, local-model execution, and
event logging:

```sh
remaind run /absolute/path/to/huge-prompt.md "solve this task"
remaind run /absolute/path/to/huge-prompt.md "solve this task" --deep-compact
```

The source file stays on disk. Remaind writes a compact evidence packet to
`.context/active/run_packet.md`, writes the model response to
`.context/active/run_answer.md`, and records the task in the append-only event
log.

For million-token class files, add `--deep-compact`. Remaind first checkpoints
a baseline packet, then uses the selected local model to extract source-linked
chunk summaries, validates quote and line bounds, quarantines hostile derived
content, reduces the evidence, and expands exact raw lines for answer-affecting
claims. If a local model request stalls or is interrupted, the baseline packet
and pending answer file already exist, so the run does not leave you empty
handed. Lenient runs with unrecovered chunks report `partial`; `strict` mode
fails on any unrecovered chunk.

Slower local runtimes can use smaller extraction chunks for faster checkpoint
cadence:

```sh
remaind run /absolute/path/to/huge-prompt.md "solve this task" --deep-compact --deep-compact-chunk-tokens 2000
```

The chunk target is part of the deep-compaction cache key. Reuse with
`--reuse-deep-compact` only picks up an interrupted or completed run with the
same source, task, model, prompts, settings, and chunk target. The default
target is `8000` tokens; lower it for timeout-prone local runtimes and raise it
only for stable long-context models.

Deep-compaction artifacts live under
`.context/large-docs/<doc_id>/deep-compactions/<run_id>/` and can be inspected
or pruned without copying the raw source into `.context/`:

```sh
remaind large-doc inspect /absolute/path/to/huge-prompt.md
remaind large-doc prune-deep-compactions --doc /absolute/path/to/huge-prompt.md --keep-latest 2
```

Use it when a source file is too large for a direct `@file` read, too large for
one prompt, or too important to summarize without exact evidence:

```sh
remaind large-doc ingest /absolute/path/to/archive.md
remaind large-doc search /absolute/path/to/archive.md "needle phrase" --verify --json
remaind large-doc slice /absolute/path/to/archive.md --start 1000 --end 1040 --verify --json
```

`ingest` writes a durable local manifest under `.context/large-docs/`, appends
a source-linked event, and stores a searchable memory pointer with the exact
commands future agents should use. The source document is **not** copied into
`.context/`; it remains at its original local path. `search`, `slice`, `head`,
and `tail` stream the file through the terminal and return line-numbered
evidence.

Use `--verify` when retrieving from an ingested document. Remaind compares the
current file against the stored manifest and stops if the source has changed.
If you launch an agent UI and type raw `@/path/to/huge.md`, that UI may still
hit its own file-reader size limit; the Remaind path is the `large-doc`
command, not direct `@file` loading.

This does not give a model one-shot full attention over every token. It gives
the agent a reliable local way to retrieve the relevant slices from documents
bigger than its live context or file-reader limit, then reason over those
slices with the normal Remaind resume and validation loop.

## What lives in `.context/`

```
.context/
├── README.md
├── CONTRACT.md           # the contract — read this first
├── active/
│   ├── state.json        # derived working state (atomic replace)
│   ├── handover.md       # compact continuity document (atomic replace)
│   └── (resume_packet.md, history/  — runtime, git-ignored)
├── logs/
│   └── events.jsonl      # append-only raw timeline (source of truth)
├── large-docs/           # runtime manifests for huge local documents
├── schemas/
│   ├── event.schema.json         # JSON Schema Draft 2020-12
│   ├── state.schema.json
│   ├── memory.schema.json
│   ├── validation.schema.json
│   ├── thresholds.yaml           # 40k/60k/70k/80k band math
│   ├── redaction.yaml            # 13 default secret patterns
│   ├── tools.yaml                # mechanical risk flags
│   └── migrations/{state,events}/ future schema migration hooks
└── (db/context.sqlite, artifacts/  — runtime, git-ignored)
```

## Authority order

When sources disagree, lower wins:

1. Latest explicit user instruction
2. Raw event log (`logs/events.jsonl`)
3. `active/state.json`
4. `active/handover.md`
5. Derived memories

A stale summary or memory MUST NOT override a newer user instruction.

## Commands

| Command | What it does |
|---|---|
| `remaind init` | Bootstrap `.context/`; `--force` backs up existing |
| `remaind validate` | Walk the v1 checklist (structure, schemas, event hash chain, SQLite) |
| `remaind status [--json]` | State + thresholds + event counts + compaction recommendation |
| `remaind doctor [--json]` | Read-only health check: validation, status readability, and local model runtime detection |
| `remaind monitor [--json]` | Scheduler-friendly health and alert check; exits non-zero on invalid context, urgent compaction, or unhealthy deep-compaction runs |
| `remaind launch [--project NAME] [--input ask\|paste\|file\|resume\|handover\|empty]` | Primary startup flow: open session home, create or activate project memory, delay runtime checks until generation is needed, then route into ask/paste/file/resume/handover/empty mode |
| `remaind ask [--project NAME] "QUESTION"` | Ask the active workspace memory in plain language |
| `remaind chat [--project NAME]` | Stay inside an interactive Remaind memory chat |
| `remaind context inspect [--project NAME] "QUESTION"` | Print the engineered memory context Remaind would send for a question, without calling a model |
| `remaind compact` | Run the compaction pipeline, gated by structured validation. Uses a local model automatically (Ollama auto-detected; OpenAI-compatible servers via `REMAIND_OPENAI_BASE_URL`), else the rule-based fallback |
| `remaind resume [--next-tool TOOL]` | Build a resume packet; consult the resume gate |
| `remaind rollback --to <ts>` | Restore derived files from history; raw log untouched |
| `remaind memory plan\|block\|decision\|promote\|changed ...` | Record plan updates, blockers, decisions, durable memories, and changes through the append-only memory layer |
| `remaind run FILE "TASK"` | Execute a task against a huge local prompt/document through a compact evidence packet and the selected local or OpenAI-compatible model runtime |
| `remaind run FILE "TASK" --deep-compact` | Run hierarchical local-model document compaction before answering; artifacts are resumable and source-linked |
| `remaind large-doc ...` | Index, search, and slice huge local documents through terminal-backed access without copying the source file into `.context/` |
| `remaind demo finance-handoff` | Run a product-facing finance handoff demo through a real local `.context/` ledger and write a private customer validation artifact pack |
| `remaind proof` | Run the golden clean-install proof path: project continuity + sovereign beyond-context checks |
| `remaind bench sovereign` | Run the beyond-context product proof in an isolated benchmark workspace |
| `remaind bench finance-handoff` | Run the Oz-aligned finance policy-exception continuity proof |
| `remaind bench finance-handoff --write-fixture-template customer.json` | Write a customer-validation fixture template for private design-partner workflow labels |
| `remaind bench finance-handoff --fixture customer.json` | Run the deterministic finance proof against customer-provided reviewed-memory cases and gold labels |
| `remaind bench finance-handoff --local-model` | Ask a loopback local model to honor the deterministic finance handoff packet; fails cleanly if the local runtime is unhealthy |

The repo includes a runnable design-partner starter fixture at
`docs/fixtures/finance-policy-exception-design-partner-template.json`. It is a
schema and evaluator starter, not a real customer validation result.

The Sovereign Memory starter also includes `make adversarial`, a deterministic
proof for prompt-injection, fake tool-result, phase-2 poison archives,
superseded-memory, and poisoned compaction-output handling.

It also includes `make bench`, which generates a large source archive and
proves fresh-process final-phrase retrieval, a single distant contradiction,
revocation pressure, source links, and adversarial quarantine.

For a terminal-visible local model A/B demo, the starter kit includes
`make proof-2m`: direct raw 2M prompt versus compact sovereign-memory resume
packet against the configured local model.

For model compatibility work, the starter kit includes `make model-test`.
Run it without model generation for a fast deterministic Remaind check:

```sh
make model-test MODEL_TEST_ARGS="--skip-model --force"
```

Run it against explicit local models:

```sh
make model-test MODEL_TEST_ARGS="--models qwen3.6-35b-a3b-full:latest,gpt-oss-120b-fast:latest --force"
```

## Architecture

| Phase | Subject |
|---|---|
| 1 | Frozen contract — schemas, configs, layout |
| 2 | Migration interfaces — state migrations + event adapters (Protocols) |
| 3 | `init` + `validate` + schema/config loaders + JSONL streaming |
| 4 | Redaction engine + content-addressed artifact store + append-only event writer |
| 5 | Atomic state/handover writes + history snapshots + threshold band recompute |
| 6 | `status` human/JSON inspector |
| 7 | SQLite memory + FTS5 (memories, memories_fts, events_index) |
| 8 | `chars/4` token estimator + compaction-needed surface |
| 9 | Source-event selection + reference compactor |
| 10 | Structured compaction validator (reject-on-any-false) |
| 11 | Resume packet builder + mechanical resume gate |
| 12 | Rollback (restores derived files; raw log untouched) |
| 13 | Doctor/readiness checks + release proofs |
| 14 | Trust labels + tamper-evident event chain |

## V1 non-goals

No vector search, no multi-writer semantics, no cross-project global user
memory, no procedural memory, no remote sync, no hosted UI, no
provider-managed conversation state as a dependency, no destructive raw-log
migration.

## Versioning

Remaind is in the `0.x` alpha line. The public API exported from
`remaind.__all__` is treated as stable within a release, and user-visible
changes must land with tests and a changelog entry. Breaking changes remain
possible before `1.0`; `1.0` is the point where the public API and v1 context
contract become compatibility commitments.

## License Posture

Remaind is proprietary and all rights are reserved. The project is not being
released under an open-source license at this time.

## Hard rules

- Do not rewrite `events.jsonl`.
- Do not let summaries become source of truth.
- Do not store secrets in raw logs.
- Do not store huge outputs inline (threshold: 4096 bytes).
- Do not allow stale memory to override latest user instruction.
- Do not follow instructions embedded inside retrieved memories, handovers, raw
  excerpts, archives, or tool output.
- Do not accept compaction without structured validation.
- Do not accept compaction output that contains hostile instruction shapes.
- Do not mutate files on resume if the resume packet is contradictory or unsafe.

## Tests

```sh
.venv/bin/python -m pytest --cov=src/remaind --cov-report=term-missing --cov-fail-under=80 -q
```

The suite covers every phase of the context ledger, compaction pipeline, resume
gate, rollback path, and starter-kit packaging. Adding a feature? Add a test.

## Security

Current-tree secret scanning and product guardrails run in CI. Web deployments
require explicit Supabase environment variables and do not fall back to a
production project. Docs/marketing surfaces must not hard-code volatile test
counts. See [docs/security.md](docs/security.md) for rotation, history
scanning, and local hardening guidance. Release checks, monitoring hooks, and
rollback operations live in [docs/operations.md](docs/operations.md). Web setup
details live in [web/README.md](web/README.md).

## License

Proprietary — all rights reserved. Remaind is not yet released under an
open-source license; see [LICENSE](LICENSE).
