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README.md

ContextLattice

ContextLattice editorial website hero showing a live local context field

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.

CLI first ContextLattice v4.0.5 Local-first runtime Apache License 2.0

Quickstart · How it works · Agent setup · Architecture · Docs · Updates

Stop replaying the brief

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.

CapabilityWhat changes
Durable continuityReopen the objective, decisions, repository state, risks, proof, and next move as one bounded packet.
Explainable retrievalRank evidence by impact per token and expose source coverage, omissions, opposition, degradation, and receipts.
Portable contextMove signed, least-privilege continuation across agents and machines while keeping execution and transport caller-owned.
Verified skill evolutionDiscover skills without loading every file, evaluate repeated wins on holdouts, and require review before promotion.
Privacy-bounded Aggregate SignalLearn 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.

How it works

StageContextLattice does
01 · ReopenReconstructs the one active mission from durable checkpoints and current state.
02 · SelectRetrieves high-signal evidence into a compact Context Pack with provenance.
03 · MoveCarries signed, bounded context through Agent Packets, Passports, and encrypted continuation envelopes.
04 · EarnRecords outcomes and promotes reusable behavior only after deterministic proof and human approval.
05 · CompoundImproves 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.

Quickstart

Requirements: macOS, Linux, or Windows through WSL2; a Compose v2-compatible container runtime; and gmake, jq, rg, python3, and curl.

1. Install

git clone https://github.com/sheawinkler/ContextLattice.git
cd ContextLattice
cp .env.example .env
gmake quickstart

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.

2. Verify the runtime and retrieval path

curl -fsS http://127.0.0.1:8075/health | jq
contextlattice doctor --pretty
contextlattice context "verify this ContextLattice installation" \
  --project contextlattice \
  --pretty

Healthy containers are only the first check. The final command exercises the actual context path and reports source coverage, degradation, evidence, and next actions.

For a fuller lifecycle proof from the repository:

scripts/agent/agent-runtime-proof-pack --pretty
scripts/agent/agent-adoption-proof-matrix \
  --skip-provider-smoke \
  --progress \
  --pretty

Connect your agents

Run integration from the repository that should use ContextLattice:

cd /path/to/your/project

contextlattice_adopt integrate \
  --repo . \
  --agents codex,claude-code,opencode,hermes-agent,hermes-ultra,omp,mercury-agent,pi,droid \
  --pretty

contextlattice_adopt integrate \
  --repo . \
  --agents codex,claude-code,opencode,hermes-agent,hermes-ultra,omp,mercury-agent,pi,droid \
  --check \
  --pretty

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.

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.

The daily agent loop

# Confirm readiness when the environment is uncertain.
contextlattice doctor --pretty

# Retrieve scoped context before substantial work.
contextlattice context "debug the current release regression" \
  --project contextlattice \
  --pretty

# Save concise, durable progress.
contextlattice remember \
  "Root cause verified; regression test added; focused checks pass." \
  --project contextlattice \
  --pretty

# Resume without replaying the transcript.
contextlattice resume --project contextlattice --pretty

# Repair stale or wrong recall without silently rewriting history.
contextlattice correct \
  "The prior deployment record is stale." \
  --category stale \
  --project contextlattice \
  --pretty

# Close the loop with the verified outcome.
contextlattice finish \
  "Regression fixed and verified." \
  --success \
  --project contextlattice \
  --pretty

Find a capability without loading every skill body:

contextlattice_skills_index search "browser automation" --pretty

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.

Architecture

ContextLattice service map ContextLattice retrieval and learning flow

The default local control path is:

Agent or application
        │
        ▼
ContextLattice CLI / HTTP / MCP
        │
        ▼
Gateway :8075
        ├── durable write and outbox fanout
        ├── scoped retrieval and source receipts
        ├── session, objective, graph, and outcome state
        └── dashboard-visible proof and operations

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.

Public and paid boundaries

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.

Install options

PathBest forStatus
Source + gmake quickstartTechnical users and terminal-capable agentsRecommended
brew tap sheawinkler/contextlattice && brew install --cask contextlatticemacOS convenience bootstrapAvailable
macOS universal DMGGuided macOS bootstrapUnsigned technical preview; expect Gatekeeper warnings
Windows x64 MSIGuided Windows bootstrapAvailable
Linux bootstrap bundleGuided Linux bootstrapAvailable

Resource profiles

ProfileCPURAMStorage
Hugging Face / Glama lite2–4 vCPU4–8 GB20–50 GB SSD
Local Lite core2–4 vCPU8–12 GB25–80 GB SSD
Local Lite advanced4–6 vCPU12–16 GB80–140 GB SSD
Local Full6–8 vCPU12–20 GB100–180 GB SSD

For heavier ingest, model storage, or the spike-lab adapters, read the installation and storage guidance before selecting a profile.

Security and privacy

  • Local-first and account-free in the public local lane.
  • API-key protection for operational routes.
  • Deterministic secret-like content filtering at write ingress: redact by default, block when configured, and allow only by explicit operator choice.
  • Provenance and trust isolation on retrieved memory.
  • Signed portable context and encrypted continuation envelopes.
  • Dry-run-first graph repair, source backfill, and quarantine workflows.
  • No automatic execution of retrieved instructions or imported continuation content.

Security reports follow SECURITY.md.

Documentation

NeedStart here
Product overviewcontextlattice.io
InstallationInstallation guide
CLI and agent lifecycleCLI reference
Harness and app integrationIntegration guide
Architecture and scalingArchitecture · Scaling memory
TroubleshootingTroubleshooting guide
Current behavior and release evidenceUpdates · v4.0.5 release notes
RoadmapPublic roadmap
Agent hooksAgent hook contract
Retrieval trustRetrieval receipts
Skills and verified learningSkill efficacy review · Skill Foundry
Portable contextContext Passport and Mesh
Local inferenceLocal model options
Full repository-backed manualPublic field manual

The current release baseline is v4.0.5.

License

ContextLattice's public lane is licensed under the Apache License 2.0.

关于 About

The local-first intelligence layer that gives AI agents durable continuity, explainable retrieval, portable context, and verified learning across harnesses.
agent-frameworkagent-memoryagent-orchestrationai-infraai-interfacecontext-engineeringcontext-managementgolanglocal-firstlong-horizon-agentslong-horizon-intelligencemcpretrievalrust

语言 Languages

Go60.0%
Python23.6%
Shell5.9%
TypeScript5.1%
Rust3.5%
CSS0.7%
PowerShell0.6%
Makefile0.4%
JavaScript0.2%
Just0.0%
AppleScript0.0%
Jinja0.0%
Batchfile0.0%

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