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Use the managed-research package when you want scripts, CI jobs, notebooks, or typed Python workflows.

​
Install and authenticate

uv add managed-research
export SYNTH_API_KEY="sk_..."

import os

from managed_research import ManagedResearchClient

client = ManagedResearchClient(api_key=os.environ["SYNTH_API_KEY"])

​
Start a one-off run

run = client.runs.start(
    "Review the project context and propose the smallest high-impact improvement.",
    host_kind="daytona",
    work_mode="directed_effort",
    providers=[{"provider": "openrouter"}],
    runbook="lite",
)

print("project:", run.project_id)
print("run:", run.run_id)

​
Wait and inspect evidence

result = run.wait(timeout=60 * 60, poll_interval=15)

print("state:", result.state.value)
print("stop reason:", result.stop_reason_message or result.stop_reason)
print("tasks:", run.task_counts())
print("actors:", run.actor_counts())

for message in run.messages(limit=20):
    print(message.get("role"), message.get("status"), message.get("body", "")[:120])

manifest = run.artifact_manifest()
print("output files:", [artifact.path for artifact in manifest.output_files])

for artifact in run.artifacts():
    print(artifact.artifact_id, artifact.artifact_type, artifact.title)

​
Create a project and preflight

project = client.projects.create(name="Improve my eval runner")
project.repositories.attach(github_repo="owner/repo")
project.context.set_project_knowledge(
    "Focus on reproducible evals, clear failure reporting, and reviewable evidence."
)

preflight = project.runs.preflight(
    host_kind="daytona",
    work_mode="directed_effort",
    providers=[{"provider": "openrouter"}],
    runbook="lite",
)

if not preflight.clear_to_trigger:
    raise RuntimeError(preflight.resolution_reason or "Run is not ready to start")

run = project.runs.start(
    "Inspect the eval runner, fix the highest-leverage issue, and explain the evidence.",
    host_kind="daytona",
    work_mode="directed_effort",
    providers=[{"provider": "openrouter"}],
    runbook="lite",
)

​
Branch from a checkpoint

checkpoint = run.create_checkpoint(reason="before trying a riskier refactor")

retry = run.branch_from_checkpoint(
    checkpoint_id=checkpoint.checkpoint_id,
    mode="with_message",
    message="Try again from this checkpoint, but optimize for the smallest patch.",
)

print("branched run:", retry.child_run_id)

​
Errors and denials

The SDK raises typed exceptions for launch-time failures. Use preflight when you want structured blockers before spending runtime. Common denials include unsupported harness/model pairs, unsupported reasoning effort, missing auth, budget caps, incomplete project setup, and provider availability.