#499 · Primary category: AI Agents & Automation

sprix-sage-router

a2a agent-orchestration agent-routing ai-agents multi-agent-systems python sprix-ai task-scheduling

Sprix AI at 屿智同行 — state-aware SELF/COLLABORATE/HANDOFF routing for A2A agent networks.

Project last updated:08/28/26

GitHub Stars

2.9K

Forks

338

Contributors

8

License

MIT

Why we included this project

Most agent frameworks stop at discovery: they tell you which agents exist, but leave the harder question of who should actually work on a task once execution is underway. SAGE Router is a decision layer on top of the Agent2Agent protocol that answers that question at runtime, choosing between letting the current agent continue, recruiting a small set of collaborators, or handing the whole task to a specialist. The choice is computed from concrete state rather than a heuristic: completed DAG nodes, reusable artifacts, observed partial quality, remaining budget, and deadline all feed into a single auditable objective. Teams building multi-agent systems that need to recover from failures or re-plan mid-task will find the checkpoint-aware rerouting and requirement-conditioned trust tracking useful, and the reference implementation has no runtime dependencies, so it is easy to prototype against. It is a research preview rather than a turnkey product, but permission-first filtering, bounded candidate search, and state persistence make it a solid starting point for production routing logic.

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