OpenAI — Codex

pip install agentfield
npm install -g @openai/codex
codex login        # OAuth in the browser, or set OPENAI_API_KEY

from pydantic import BaseModel
from agentfield import Agent, HarnessConfig

class ScaffoldResult(BaseModel):
    files_created: list[str]
    notes: str

app = Agent(
    node_id="scaffolder",
    harness_config=HarnessConfig(
        provider="codex",
        model="gpt-5-codex",
        permission_mode="auto",   # Codex applies edits without prompting
        max_turns=20,
        max_budget_usd=0.30,
        cwd="./generated",
    ),
)

@app.reasoner()
async def scaffold_module(spec: str) -> dict:
    result = await app.harness(
        f"Scaffold a Python module that satisfies this spec:\n\n{spec}",
        schema=ScaffoldResult,
    )

    if result.is_error:
        return {"ok": False, "error": result.error_message}

    return {
        "ok": True,
        "files": result.parsed.files_created,
        "notes": result.parsed.notes,
        "cost_usd": result.cost_usd,
        "num_turns": result.num_turns,
    }

impl = await app.harness(
    f"Implement this feature:\n\n{spec}",
    provider="codex",
    permission_mode="auto",
    schema=ImplResult,
)

if impl.is_error:
    raise RuntimeError(impl.error_message)

review = await app.harness(
    f"Review these changes for correctness and edge cases:\n\n{impl.parsed.diff}",
    provider="claude-code",
    permission_mode="plan",
    schema=ReviewResult,
)

if review.parsed.severity == "high":
    # Loop again with the reviewer's findings as input.
    ...