Solo is a closed-loop orchestrator for opencode that delegates code changes to specialized subagents and iterates based on raw test results to pass target tests.

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31

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Forks

3

Open issues

0

License

MIT

Last updated

2026-07-08

AI repository intelligence
FR-AI / ANALYSIS

Why it is worth attention

It introduces a cost-efficient tiered architecture with context isolation, achieving expert-level orchestration on complex tasks while consuming significantly fewer tokens from costly models.

Who it is for

  • Developers using opencode for software development
  • Teams working on bug fixes or multi-file code changes
  • Users seeking to reduce LLM costs without sacrificing quality
  • AI agent developers interested in multi-agent orchestration

Use cases

  • Automated bug-fix iteration with real test feedback
  • Long-horizon multi-file refactoring or feature implementation
  • Codebase exploration and root cause analysis
  • Adversarial verification of large or risky changes

Strengths

  • Closed-loop feedback directly from test output ensures targeted fixes
  • Context isolation reduces expensive model token usage by keeping heavy tool outputs in subagent sessions
  • Modular agent design allows swapping models and behaviors per agent
  • Validated on SWE-bench Verified with 70% resolution rate and lower effective cost via tiered routing

Considerations

  • Requires opencode platform and configured LLM providers
  • Performance on simple single-file bug fixes is comparable to monolithic agents (no significant advantage)
  • Potential stall timeouts in automated runs (5 out of 50 instances in benchmark)

README quick start

Quick Start

Description

OpenCode agent configuration — a read-only orchestrator delegates to 6 specialized subagents. Expert model plans, fast models execute. Isolated contexts, minimal permissions, adversarial verification built in. Ready to drop in.

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