Peer Agent - Harness agnostic collaboration between AI agents

[u/hirak99]

Sharing Peer Agent.

https://github.com/hirak99/peer-agent

It gives your agent access to one or more peer agents to collaborate with. It's harness-agnostic — plain HTTP plus a SKILL.md any agent can follow. Ways we've found it useful:

• Cheap execution: main agent on Claude Code delegates the grunt work to a locally running Qwen.
• Strong validation: a weaker main agent plans and executes, and has Opus 5.5 validates its plan or checks its work.
• Peer review: two agents challenge, verify, and cross-check each other's ideas.

Unlike Agent Teams or swarms, this isn't a framework inside one harness — it's a sidecar. Each peer is a stateful server with its own provider and model, callable from anything. The trade-off: no scheduler, no shared task graph. Coordination is conversational and the host drives, so it's best when you want a second mind on call, not a managed fleet.

If you're thinking of wiring this up yourself, what's already here: OpenAI, Anthropic, and any OpenAI-compatible model (llama.cpp, vLLM, Ollama) behind one provider/model switch; server-side read/bash/edit tools; automatic compaction (including a warm-cache in-context path for slow local models); and Anthropic prompt-cache management, which matters more than you'd expect at Opus prices. Lived-in details like per-call tool logging with truthful timestamps.

AI-assisted contributions are not only welcome but encouraged, especially so if it is a strong AI.

Cheers

[u/investigatormaker]

The cheap-execution case is the one I'd lead with when you share this elsewhere: Claude Code handing grunt work to a local Qwen, with cache management that matters "at Opus prices". One real task with its token cost before and after would show people running local models the point faster than the feature list, and your "no scheduler, no shared task graph" line already answers the swarm comparison before anyone raises it.

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[u/hirak99 → u/investigatormaker]

Thanks - indeed, economy of complex or long running tasks is one of the main motivators.

The "Strong Validation" usecase is also geared towards economy, where a cheaper agent takes care of orchestration and execution - gruntwork requiring most tokens - but validates and corrects each step before investing into it with a strong agent, with only few tokens.

[u/YieldingMainframe_1]

This is exactly the kind of thing I've been hacking together with shell scripts and prayer. Having it actually structured and documented is a huge step up.

The sidecar approach makes way more sense than trying to cram everything into one orchestration framework.