Agent OS · Component · research-agent-orchestration
Policy-aware research agent orchestration
What it does
Plan and run session continuations, dispatch research/memo/jobs, request approvals and record agent action contracts and execution traces through API/SDK.
Core pattern
Research goal orchestration + human approval and step traces
- Input
- Agent research objective and policy context
- Output
- Plan, executed research steps, approval state and trace
Key parameters
| Name | Type | Default | Values |
|---|---|---|---|
| objective | string | — | — |
| max_steps | integer | 5 | 1–100 |
| action_input | object | {} | — |
| approval_id | — | — | — |
| require_approval | boolean | true | false · true |
Maturity and limits
Runner calls policy/approval/job services and persists traces; agent/orchestration tests present. Source paths were inspected statically; tests and live integrations were not executed. This rating describes implemented code, not production validation.
No project license found. External market/news data have licensing, rate-limit and availability constraints. Research only: no trading execution. Backtests can be biased and cross-asset semantics vary. Static inspection; tests not run.
Used in pipelines
Industry tags
- FinanceSource-supported industry
For work involving research materials and financial service operations, use research goal orchestration followed by human approval and step traces.
- Legal servicesTransferable use
For ongoing research into case issues and regulatory materials, use research goal orchestration followed by human approval and step traces.
Skills pack
Contract scaffold and deterministic mock
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