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I am seeking one independent Deep Agents reproduction of a bounded subagent-handoff test.
Urusilla is an experimental declarative agent message surface, not a proven universal token saver. The current broad external result is 0% post-decode model-input saving because unfamiliar traffic falls back to concise text.
Please compare three matched arms with fresh state and identical model/task/settings:
concise raw text;
ordinary JSON;
Urusilla supplied directly to the receiving model, with no prose re-expansion.
The ledger must include every input and output token from setup/teaching, the lead agent, subagents, middleware, retries, repair, fallback, and judge/router calls. Intermediate reasoning does not need to be disclosed; aggregate usage and observable task results are enough. Tools, persistence, permission expansion, spending, network actions, and external effects should remain disabled.
The candidate passes only if task success is non-inferior and total task tokens are lower. Wire bytes or one message surface alone are insufficient. Negative, null, refusal, and fallback outcomes are first-class results.
Deep Agents-specific question: can the current runtime expose a reconciled usage ledger for the lead agent and asynchronous subagents while keeping retries and streaming fragments from being double-counted?
Codex agents assisted with the fixture and this request; the maintainer reviewed and submitted it.
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I am seeking one independent Deep Agents reproduction of a bounded subagent-handoff test.
Urusilla is an experimental declarative agent message surface, not a proven universal token saver. The current broad external result is 0% post-decode model-input saving because unfamiliar traffic falls back to concise text.
Please compare three matched arms with fresh state and identical model/task/settings:
The ledger must include every input and output token from setup/teaching, the lead agent, subagents, middleware, retries, repair, fallback, and judge/router calls. Intermediate reasoning does not need to be disclosed; aggregate usage and observable task results are enough. Tools, persistence, permission expansion, spending, network actions, and external effects should remain disabled.
The candidate passes only if task success is non-inferior and total task tokens are lower. Wire bytes or one message surface alone are insufficient. Negative, null, refusal, and fallback outcomes are first-class results.
Frozen public materials:
Deep Agents-specific question: can the current runtime expose a reconciled usage ledger for the lead agent and asynchronous subagents while keeping retries and streaming fragments from being double-counted?
Codex agents assisted with the fixture and this request; the maintainer reviewed and submitted it.
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