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A experimental coding harness for VSCode based on Opencode. Optimized for minimizing content without harming quality.

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Relo Code

Relo Code is a context-managed multi-agent AI software engineering system for Visual Studio Code.

Relo is not a chat log with extra buttons. It treats model context as mutable computational state. Agents keep their identity while Relo rebuilds, compresses, replaces, and garbage-collects what the model actually sees.

Variable Context Engine  →  Multi-Agent Orchestrator  →  OpenCode runtime  →  Models + tools
  • Relo orchestrates. Task graphs, agent hierarchy, context generations, memory, verification, worktrees.
  • OpenCode executes. Provider access, model calls, tools, filesystem, shell.
  • VS Code presents. Chat, trees, diffs, approvals, settings.

Why variable context matters

Long-running agents rot because transcripts only grow:

request + exploration + tool dumps + stale plans + failures + more messages

That produces forgotten constraints, repeated mistakes, circular reasoning, and wasted tokens. Relo constructs a fresh context generation from durable task state, verified findings, relevant code, and recent failures — not from the entire history.

Architecture

Visual Studio Code  --stdio JSON-RPC-->  Relo Core (Go)
                                              |
                                              | HTTP + SSE (documented OpenCode API)
                                              v
                                        OpenCode serve

See docs/architecture.md and docs/context-engine.md. Agents work in virtual workspaces by default, which lay files out on disk only when a tool needs real files; Git worktrees, the opt-in alternative, are described in docs/worktrees.md, and virtual workspaces in docs/virtual-workspaces.md. A proposal for running part of the work on a native runtime next to OpenCode is in docs/hybrid-runtime.md. How Relo tells which models can see images, and how agents view screenshots, is in docs/vision.md. Running agents on your installed Claude Code CLI, with its own sign-in, is in docs/claude-code.md.

Quick start

On Linux, with Go, Node.js 20+, VS Code and opencode 2.x installed:

make dev        # build, package and install the extension into VS Code
make preflight  # read-only environment checklist

Full guide (install, models, free smoke-test model opencode/cat-jam-free, mock runtime, logs, reporting issues): docs/quickstart.md.

Go version is read from core/go.mod (currently Go 1.25). Other requirements: Node.js 20+, VS Code 1.90+, Git (for worktrees), OpenCode on PATH for live models (relo.runtime=mock works without it).

Development

make dev      # build + package + install into VS Code (Linux)
make vsix     # build .vsix only (no install)
make build    # core + extension + webview
make test     # go test ./... and TypeScript tests
make lint     # go vet, gofmt check, tsc
make package  # cross-compile cores + vsix

Launch configs:

  • Run Extension
  • Debug Relo Core
  • Debug Extension + Core

Core stdio IPC is versioned (v: 1). Logs go to stderr; stdout is IPC only.

Building / testing / packaging

Command What it runs
make core Host-platform relo-core into extension/bin/
make core-all linux-amd64, windows-amd64, darwin-arm64, darwin-amd64
make test Go tests including the mock acceptance scenario
make package VS Code extension with bundled cores

From core/: go test ./...

From extension/: npm test and npm run compile

Troubleshooting

Relo: Failed — open Relo: Open Logs. Confirm relo-core exists (make core) and the workspace is writable for .relo/relo.db.

OpenCode missing — install from https://opencode.ai/docs or set relo.openCode.path. Relo still starts on the mock runtime.

No models — authenticate providers inside OpenCode, then Relo: Restart Backend.

Agents stuck — Relo: Pause / Resume, Stop All Agents, or Refresh Primary Context.

Dirty Git files — Relo snapshots user modifications at session start and will not apply patches that overwrite them.

License

MIT

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A experimental coding harness for VSCode based on Opencode. Optimized for minimizing content without harming quality.

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