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Agents2026-07-12 · source-backed
The failure mode is a well-formed but policy-forbidden call, cancel a booking, change a passenger count, that neither the tool nor the agent's self-report flags (arXiv). In the airline domain tested, the fix wasn't more reasoning. It was cheap, read-only deterministic gates that check the state transition against domain policy before the write commits. Wrap high-stakes tool calls in explicit precondition checks. Don't trust the model to police itself.
Each link below shares sources, entities, or timing with this story.
arXiv 2608.02764 targets agents that issue refunds, reserve inventory and move money, where budgets and approval status change between authorization and effect. The authors define policy-state serializability: committed effects must be explainable as authorized against the pol...
Across 2,823 committed episodes on three frameworks, a one-class echo-state-network ensemble with CUSUM alarms catches 71% of mid-episode failures at a 5% false-alarm budget, three orders of magnitude cheaper than a judge call. But learned monitors don't transfer (AUROC 0.527...
If you run a production MCP server, you have a hard deadline. The 2026-07-28 spec removes the protocol-level session model entirely, and it's a breaking change. The MCP release candidate makes every request carry its own protocol version, client info, and capabilities (Model C...
ECP captures agent outputs, tool invocations, and audit context uniformly, with adapters for LangChain, LlamaIndex, CrewAI, and PydanticAI so the same checks run against any of them. arXiv The authors explicitly label it work-in-progress with the method set expected to change....
arXiv 2608.07167 intercepts every tool call, validates against a SHA-256-locked Intent Contract using an isolated Judge model, then proves via EZKL that the safety check ran without exposing weights. F1 88.5% at a 1.1% false-positive rate on Agent-SafetyBench. Generation costs...
arXiv 2608.06370 evaluated models emitting code that calls tools against JSON-schema tool calling on BFCL v4. PTC matched or exceeded the baseline in 11 of 14 models, with the GPT-5.6 family up 10.6%, and held stable under parallel execution in 13 of 14. Under context degradat...
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