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Documentation Index

Fetch the complete documentation index at: https://docs.usesynth.ai/llms.txt

Use this file to discover all available pages before exploring further.

Managed Research is organized around durable work rather than chat turns.

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Project

A project is the reusable control unit for repo bindings, files, datasets, credentials, notes, knowledge, budgets, and policy. Use a project when workers need persistent context or repeated runs.

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Run

A run is one execution of a goal against the current project and launch configuration. Runs are inspectable through state, messages, logs, task counts, actor status, artifacts, checkpoints, usage, questions, approvals, and final reports.

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Worker

Workers execute research or engineering tasks inside managed workspaces. The orchestrator can create tasks, assign workers, coordinate reviewers, and synthesize outcomes depending on runbook and work mode.

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Evidence

Evidence is the durable record that makes Managed Research different from a chat transcript:
  • runtime messages
  • task and actor state
  • logs and logical timeline
  • checkpoints and branches
  • artifact manifest and file outputs
  • usage and budget state
  • PRs, reports, and final outputs

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Launch configuration

Launch fields shape a run:
  • host_kind chooses the execution substrate.
  • work_mode chooses goal posture.
  • runbook chooses collaboration posture.
  • providers bind runtime provider capability.
  • agent_harness, agent_model, and agent_model_params choose public agent runtime settings.
Backend preflight remains authoritative for whether a launch is allowed.

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Supported integration paths

Use MCP for agent-client workflows and the Python SDK for scripts. Direct /smr REST wiring is internal and unstable.