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Vivary

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Typed memory and gates for AI-agent projects. A standard plus a scaffolder that wires up a normalized, agent-native workspace from standalone modules — typed project memory, visible state, reusable skills, private boundaries, and verification gates — whether the workspace is a second brain, a coding project, or a writing project. Think create-t3-app, but for an AI agent's workspace instead of a web app.

A vivary is an archaic word for a vivarium: a self-contained world where living things are kept, in stacked layers. That's the metaphor — your project lives inside a small, well-formed world with a substrate, an atmosphere, and gates.

Release status: 0.2.5 is current for the scaffolder (create-vivary / @vivary/create), 0.2.3 for vivary-tropo, 0.2.2 for vivary-exo, and 0.1.0 for vivary-ozone. Use 0.2.5 for new scaffolds. This package set carries the security-hardening batch for scaffold privacy ignores, symlink/out-of-root writes, hard-link-safe rewrites, and private heartbeat reports.

Surface Current Link
create-vivary (PyPI) 0.2.5 PyPI
@vivary/create (npm) 0.2.5 npm
vivary-tropo 0.2.3 PyPI
vivary-ozone 0.1.0 PyPI
vivary-exo 0.2.2 PyPI
Docs site live vivary.vercel.app
CI ci workflow GitHub Actions

Versions are intentionally independent across the four layers: create-vivary moved the most because it owns the scaffold and npm launcher, tropo and exo took the security write-boundary patches, and ozone stayed at 0.1.0 because this release did not change the review CLI.

Public Signals

Vivary public usage snapshot

Vivary tracks public npm, PyPI, and GitHub signals through reviewed daily PR snapshots. The chart is generated from stats/latest.json and stats/history.csv; see docs/SIGNALS.md for sources and caveats.

tropo (typed knowledge graph + search + storage), strato (agent OS), ozone (graph-aware review), and exo (coordination) are composed by create-vivary. See HANDOFF.md to continue, docs/ARCHITECTURE.md for the full model, and docs/PORTFOLIO.md for proof and case-study material.

Current command surface:

  • create-vivary init / doctor / wizard
  • tropo check / graph / query / migrate / init --packs
  • ozone review / impact
  • exo board / conflicts / claim / roles

Quickstart

Scaffold a workspace in one npm command. No Python package install first; the launcher needs Python 3.11+ and uv or pipx available:

npm create @vivary@latest my-workspace        # pick: second brain · coding · writing

Or install the CLIs from PyPI (run on demand with uvx, no install needed):

pip install vivary-tropo vivary-ozone vivary-exo create-vivary==0.2.5
create-vivary init my-workspace --preset coding     # interactive wizard on a TTY
create-vivary init my-codebase --preset coding --active-context cocoindex-code
create-vivary doctor my-workspace
uvx vivary-tropo check --root my-workspace

# Agent-mode — fully non-interactive, outputs JSON:
create-vivary init . --preset coding --auto --size large --yes --json

The scaffolder writes a full workspace shell: AGENTS.md, STATE.md, SOUL.md, private USER.md/MEMORY.md boundaries, private heartbeat report storage, strato runtime skills for Claude/Codex-style agents, a tropo.toml, a starter typed graph, and (optionally) a .vivary/storage.toml for LanceDB or cloud storage. Generated modules are directories with index.md routers (modules/<id>/index.md) so agents load the smallest useful context first. doctor validates the shell, active privacy ignore rules, graph health, storage backend, and module index coverage after creation. tropo query and tropo migrate power graph search and backend switching.

For coding workspaces that need richer source retrieval, --active-context cocoindex-code adds optional CocoIndex-code guidance and graph nodes. It does not auto-install, index, enable MCP, or send source text anywhere; the generated skill asks before those gates, then gives the approved ccc init / ccc index / ccc search path. See docs/ACTIVE-CONTEXT.md.

Run from source (no install)
python packages/create-vivary/create_vivary.py init sandboxes/coding-demo --preset coding
python packages/create-vivary/create_vivary.py doctor sandboxes/coding-demo
python packages/tropo/tropo.py check --root sandboxes/coding-demo
python packages/tropo/tropo.py graph --root sandboxes/coding-demo --json

The irreducible baseline

Every agent workspace, regardless of stack or task, needs the same small core:

A self-improving loop running over a typed, navigable knowledge graph, with one visible state surface and human gates.

Everything Vivary ships is a facet of that one sentence. The design law (inherited from throughline): the framework must cost almost nothing to load, or it steals the context the work needs.

That means Vivary is deliberately DRY: one fact gets one owner, while AGENTS.md, STATE.md, and module index.md files route to deeper context instead of duplicating it. Full context management is valuable only when it keeps the active context small.

No lock-in. A workspace is plain Markdown + YAML and a few CLIs — it works in any editor, or none, and on any agent runtime (Claude Code reads .claude/skills/, Codex reads AGENTS.md + .agents/). Obsidian, an IDE, a particular agent — all optional. The visual knowledge graph renders editor-free with tropo view; Obsidian fans get an opt-in setup (create-vivary init … --obsidian) — see docs/OBSIDIAN.md.

Modules

Standalone Python packages (vivary-* on PyPI), plus the npm scaffolder @vivary/create, composed by create-vivary:

Package Layer Job Source
tropo troposphere — the living foundation typed knowledge graph: what the workspace knows loam ✓
strato stratosphere — the stable layer agent OS: state surface, memory, the loop, gates, self-improvement throughline + flywheel
ozone the protective filter review — graph-aware, code and editorial new ✓
exo the outermost layer coordination — conflict detection, work claiming, role contracts new ✓

create vivary → pick a preset (second brain · coding · writing) → it lays down tropo + strato and whichever optional layers fit. See Quickstart above to install.

Documentation

Website: vivary.vercel.app — or browse the source in docs/:

The value-add (why this isn't another harness)

  1. The substrate is a typed, validated knowledge graph, not flat memory.
  2. Every change shows its blast radius — before and after — beyond a text diff.
  3. It's medium-agnostic: the same graph + review serves code and prose.
  4. It standardizes the agent workspace — which nobody has done.
  5. Agents can self-configure from scratch--auto --yes --json gives a zero-prompt, machine-readable setup path for storage, installs, and scaffolding.

License

MIT — see LICENSE.

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Typed memory, search, and gates for AI-agent workspaces. Scaffold plain-Markdown project memory, state, skills, and review gates in one command.

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