Sponsio: Deterministic Contract Layer for LLM Agents [P]

Reddit r/MachineLearning 05/25/26, 01:02 AM Tools

contract-layer tool-call-boundary llm-agents open-source deterministic production

Summary

Sponsio is an open-source deterministic contract layer that enforces tool-call boundaries and rules for LLM agents, addressing production reliability issues that prompt engineering and post-hoc auditing cannot fully solve.

We've been trying to put LangGraph agents into production for a while. The thing that kept biting us was tool-call boundary enforcement: stuff like "must call X before Y", "max N retries", "approval gate before destructive action". Worked fine in demos, broke at the moments that mattered. What we tried first: Prompt engineering. Told the model "always call check\_policy before issue\_refund". Worked \~95% of the time. The 5% that didn't was exactly the cases an auditor would ask about. Not a great answer when someone wants to know why a refund went through. Post-hoc audit (OTEL + log). Caught violations after the fact. By then the side effect already happened. Refunding the refund is awkward. Pulling everything into a workflow engine (Temporal, or nano-vm more recently). Strong guarantees but you rewrite the agent against their runtime. Too much for our use case. What we ended up with: A contract layer at the tool boundary. YAML rules, deterministic eval, runs before the tool call commits. Open-sourced as Sponsio. Repo: [github.com/SponsioLabs/Sponsio](http://github.com/SponsioLabs/Sponsio) Would love feedback from anyone running agents in prod.

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