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Feature proposal: inherited recursion-depth budget for Agent.as_tool delegation

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python
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ai, backend

Hướng nghiên cứu

Start with Agent.as_tool() in src/agents/agent.py, then trace how nested calls create Runner.run() and Runner.run_streamed() executions and how their turn limits are resolved. Review the existing runtime governance discussion #2775 and per-agent max_turns request #551 before deciding whether the proposed inherited depth limit fits the SDK. Done means maintainers settle the scope and semantics, including concurrent task inheritance and resumed workflows.

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Mô tả

Summary

I would like to propose an opt-in, inherited delegation-depth limit for Agent.as_tool() to help applications bound recursive or multi-agent delegation trees.

This is not a claim of a security vulnerability or a defect in max_turns. I understand that max_turns limits an individual Runner.run(), and a nested agent tool starts another run. The motivation is to offer an explicit SDK-side safety primitive when applications require a depth limit over a delegation chain, rather than just each run.

Reproduced behavior (no API access)

I ran a fully offline agents.testing.ScriptedModel test against public main commit cd26bbbc52847845fde73b9952b51e62e2bcbdc0 (v0.24.0 source) using distinct call IDs and a deliberately finite, four-delegation script.

  • Outer Runner.run(..., max_turns=1)
  • Recursive Agent.as_tool(..., max_turns=1)
  • Unmodified SDK: 5 model calls occur before the outer run raises MaxTurnsExceeded. This is consistent with per-run limits.
  • Candidate guard with max_agent_tool_depth=1: 2 model calls occur; the next nested agent tool fails before starting another child run, including through streaming.

The source boundary is Agent.as_tool() in src/agents/agent.py, where each nested invocation creates its own Runner.run() / Runner.run_streamed() with a separately resolved turn limit.

Proposed narrow, compatible implementation
  • Append optional max_agent_tool_depth: int | None = None to Agent.as_tool(). None preserves current behavior.
  • Track active agent-tool depth in an async context using ContextVar, with finally reset.
  • Propagate a configured limit through other agents' as_tool() wrappers, even if those descendants do not configure a limit. Children may tighten but cannot relax an inherited bound.
  • Reject excessive delegation before another child run is started.
  • No dependencies, persisted-state changes or wire-protocol changes.

Reproducible public research repository: https://github.com/BlackRonin-coder/openai-agents-recursive-budget-research

It contains the unmodified SDK reproducer, opt-in two-file patch, synthetic tests, and local verification log. The published candidate passed 1,188 relevant tests, 63 skipped, on macOS with Python 3.12.15; Ruff checks and a pristine-source patch-application check passed. I am not claiming comprehensive CI, independent validation or OpenAI endorsement.

Limitations and maintainer questions

This is a nesting-depth limit, not a root-owned cumulative model-turn, token, cost, wall-clock or cross-process execution budget. Application-initiated independent Runner.run() calls are outside this implementation. Further review is needed around concurrent task inheritance and resumed/persisted workflows.

  1. Would an opt-in inherited agent-tool depth limit be useful as a first-class SDK control?
  2. Or would you prefer a root-owned, cumulative execution budget with explicit checkpoint/cancellation semantics?
  3. If there is an existing supported mechanism addressing this exact delegation-depth use case, I would welcome a pointer and will revise or close the proposal.

Related but broader prior art: runtime governance discussions (e.g. #2775), and the existing per-agent max_turns feature request (#551). I did not find a directly equivalent recursive delegation-depth control in the currently indexed issues/PRs. This is offered as independently reproducible engineering research, not a claim of being the first person to explore recursive agent budgets.

Thank you for considering it.

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