# Human-in-the-loop - OpenAI Agents SDK

## Metadata

| Field | Value |
|---|---|
| Institute | Molodetz Institute — Research & Retrieval Division |
| Subject | agent-goal-verification |
| Document type | Source Dossier |
| Tier | 1 |
| Source title | Human-in-the-loop - OpenAI Agents SDK |
| Source URL | https://openai.github.io/openai-agents-python/human_in_the_loop/ |
| Source publisher / author | OpenAI |
| Source type | vendor docs |
| Source date (published) | Unknown — not stated (living documentation page) |
| Date researched | 2026-10-18 |
| Researched by | tai (agent), model: Muse Spark, on behalf of retoor |
| Research method | direct page fetch |
| Confidence | High |
| Status | Active |

## Summary

The official Agents SDK guide describes the industry-standard approval loop: tools declare `needs_approval`, the run pauses with pending items in `interruptions`, the app approves or rejects (optionally with a custom rejection message fed back into the run), and the same run resumes from serialized state.

## Key findings

- "Set `needs_approval` to `True` to always require approval or provide an async function that decides per call."
- "Callable approval rules fail closed when the SDK cannot safely inspect the arguments. If the arguments are missing, empty, contain only whitespace, are malformed JSON... the callable is not invoked and the call requires manual approval."
- "By default, a rejected tool call returns the SDK's standard rejection text back into the run" with per-call `rejection_message` override taking precedence over the run-wide formatter.
- "Convert the result to a `RunState` with `result.to_state()`, call `state.approve(...)` or `state.reject(...)`, and then resume", and the resumed run continues where it left off.
- Per-call approvals are scoped to the call ID; `always_approve` / `always_reject` persist the decision for the tool identity.

## Pros / strengths

- First-party specification of the dominant approval pattern, including the fail-closed rule and the denial-feedback mechanism.
- The pause / serialize / resume shape matches tai's turn-state plus `--resume` design almost exactly.

## Cons / limitations / caveats

- SDK-specific mechanics (RunState, interruptions) that tai reimplements in its own vocabulary; no guidance on free-text approval prompts or typo handling at a CLI.
- No discussion of approval fatigue or input validation; those come from practitioner sources, not this page.

## Relevance to tai

Confirms three tai design choices as industry-standard: per-command approval with an always-allow escape hatch, denial text fed back into the run as corrective context (tai's `Denied` guidance), and resumable paused runs (tai's open turn state plus `--resume`). The fail-closed rule supports keeping destructive approvals strict while recovering only the shell case on unambiguous affirmation.

## Changelog

| Date | Change |
|---|---|
| 2026-10-18 | Initial dossier created. |