The full upstream README, mirrored here for reference. Install config, tool schemas, adoption signals, and an original overview live on the ContextLattice listing page.
Open an agent. Already there.
The local-first intelligence layer that gives AI agents durable continuity, explainable retrieval, portable context, and verified learning across harnesses.
Quickstart · How it works · Agent setup · Architecture · Docs · Updates
Models can reason. Harnesses can act. Neither reliably retains the mission when a chat, model, tool, account, or computer changes.
ContextLattice gives that work a durable, inspectable context layer. It reconstructs the active objective, selects the evidence that matters, carries it safely, and records what actually worked—without turning every prompt into a transcript dump or making cloud storage mandatory.
| Capability | What changes |
|---|---|
| Durable continuity | Reopen the objective, decisions, repository state, risks, proof, and next move as one bounded packet. |
| Explainable retrieval | Rank evidence by impact per token and expose source coverage, omissions, opposition, degradation, and receipts. |
| Portable context | Move signed, least-privilege continuation across agents and machines while keeping execution and transport caller-owned. |
| Verified skill evolution | Discover skills without loading every file, evaluate repeated wins on holdouts, and require review before promotion. |
| Privacy-bounded Aggregate Signal | Learn from explicitly opted-in, clipped statistics while raw memory remains local; production activation stays hard-blocked pending independent privacy and utility review. |
The CLI is the primary interface. The dashboard makes behavior and proof visible. HTTP and MCP are companion integration surfaces for applications and harnesses.
| Stage | ContextLattice does |
|---|---|
| 01 · Reopen | Reconstructs the one active mission from durable checkpoints and current state. |
| 02 · Select | Retrieves high-signal evidence into a compact Context Pack with provenance. |
| 03 · Move | Carries signed, bounded context through Agent Packets, Passports, and encrypted continuation envelopes. |
| 04 · Earn | Records outcomes and promotes reusable behavior only after deterministic proof and human approval. |
| 05 · Compound | Improves future retrieval while preserving corrections, contradictions, freshness, and retirement semantics. |
ContextLattice does not replace your agent harness, choose goals from retrieved text, or execute imported context. Local tools remain execution surfaces; memory and remote content remain evidence.
Requirements: macOS, Linux, or Windows through WSL2; a Compose v2-compatible container runtime; and gmake, jq, rg, python3, and curl. The tested macOS baseline uses OrbStack through its explicit Docker context; see the container runtime decision.
gmake quickstart is the prescribed technical install path; installers are bootstrap alternatives. The command prepares environment wiring, asks for a runtime profile, launches the selected local stack, and validates initial readiness.
Healthy containers are only the first check. The state command verifies the canonical gateway-owned storage inventory; the final command exercises the actual context path and reports source coverage, degradation, evidence, and next actions. Existing installs can use the explicit, reversible procedure in gateway state migration.
For a fuller lifecycle proof from the repository:
Run integration from the repository that should use ContextLattice:
The integration command writes bounded managed blocks while preserving existing instruction text. It does not install Codex, Claude Code, OpenCode, Hermes, OMP, Mercury, Pi, Droid, or another third-party agent harness.
External provider discovery is network-free. Provider execution remains explicit and caller-authorized; see the external-provider boundary.
If an agent is performing the installation, it should follow the quickstart directly, avoid cloning a second checkout when already inside one, report the exact failing command and path, and rerun the deterministic check after any repair.
Continuous Cognition is advisory-only: each invocation makes one bounded request, returns opaque evidence references, and never dispatches a runner or performs an external mutation. Context-preparation claims stay in an owner-only file and cross the completion/failure boundary only through the protected header; successful explicit use consumes the artifact once.
Find a capability without loading every skill body:
The active Skills Index scans configured Codex, Hermes, Hermes Ultra, and shared
agent roots read-only. It reports each harness and root inventory separately,
collapses byte-identical SKILL.md files by SHA-256 digest while retaining every
source path as provenance, and requires discriminating query-term coverage
instead of ranking generic words such as skill, index, or agent.
Quarantine discovery remains separate, read-only by default, and never
auto-promotes retrieved content.
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The default local control path is:
Writes are validated and durably persisted before fanout. Retrieval merges the available sources, ranks bounded evidence, and reports missing or degraded coverage instead of hiding it.
The active application path is Go and Rust. Python remains in build, development, migration, and audit tooling rather than the live request path. The exact runtime and toolset choices are recorded in the v4 runtime decision and container decision.
The public local lane is account-free and useful on its own. It includes the CLI-first memory lifecycle, Context Packs, sessions, graph and claim surfaces, Skills Index discovery, Agent Packets, public Passport and Mesh contracts, and local proof tooling.
Paid artifacts add governed collaboration, protected activation, workspace operations, advanced analytics, and hosted distribution. They do not turn local memory into a mandatory cloud dependency.
See plans and distribution boundaries for the current contract.
macOS technical preview: unsigned DMG bootstrap launcher; expect Gatekeeper warnings until Developer ID notarization is configured, and prefer the source/CLI path.
| Path | Best for | Status |
|---|---|---|
Source + gmake quickstart | Technical users and terminal-capable agents | Recommended |
brew tap sheawinkler/contextlattice && brew install --cask contextlattice | macOS convenience bootstrap | Available |
| macOS universal DMG | Guided macOS bootstrap | Unsigned technical preview; expect Gatekeeper warnings |
| Windows x64 MSI | Guided Windows bootstrap | Available |
| Linux bootstrap bundle | Guided Linux bootstrap | Available |
| Profile | CPU | RAM | Storage |
|---|---|---|---|
| Hugging Face / Glama lite | 2–4 vCPU | 4–8 GB | 20–50 GB SSD |
| Local Lite core | 2–4 vCPU | 8–12 GB | 25–80 GB SSD |
| Local Lite advanced | 4–6 vCPU | 12–16 GB | 80–140 GB SSD |
| Local Full | 6–8 vCPU | 12–20 GB | 100–180 GB SSD |
For heavier ingest, model storage, or the spike-lab adapters, read the installation and storage guidance before selecting a profile.
Security reports follow SECURITY.md.
| Need | Start here |
|---|---|
| Product overview | contextlattice.io |
| Installation | Installation guide |
| CLI and agent lifecycle | CLI reference |
| Harness and app integration | Integration guide |
| Architecture and scaling | Architecture · Scaling memory |
| Troubleshooting | Troubleshooting guide |
| Current behavior and release evidence | Updates · v5.0.2 release notes |
| Roadmap | Public roadmap |
| Agent hooks | Agent hook contract |
| Retrieval trust | Retrieval receipts |
| Skills and verified learning | Skill efficacy review · Skill Foundry |
| Portable context | Context Passport and Mesh |
| Local inference | Local model options |
| Full repository-backed manual | Public field manual |
The current release baseline is v5.0.2.
ContextLattice's public lane is licensed under the Apache License 2.0.