Designing an Effective Activity Timeline for Trading Agents
Learn how to structure a clear, trustworthy timeline that shows a trading agent’s actions, limits, and errors while keeping users informed of risks.
Produced with automation, then checked by deterministic quality rules and an independent source-grounded review before publication.
- 01The timeline must show each action with a timestamp, source, and outcome.
- 02Explicit limits and policy checks should be displayed alongside the corresponding orders.
- 03Error states need clear labels and links to detailed diagnostics.
- 04Reconciliation steps are essential after every order to confirm state consistency.
- 05Users should be able to pause or stop the agent, but position closure requires separate owner review.
An activity timeline for a trading agent should list each order, limit check, and error in chronological order, showing when it happened, what data drove it, and the result. It must also surface policy limits and any manual interventions so users can see both automated decisions and human overrides.
What information should the timeline display?
The core of a useful timeline is a record of every trade‑scoped action. Each entry needs a precise timestamp, the market data source, the order parameters, and the final status (filled, partially filled, rejected, etc.). Including the source and freshness of market data helps users assess reliability, especially when data gaps occur.
- Timestamp with timezone and source identifier.
- Order details: side, size, price, venue reference.
- Limit verification result (passed, failed, reason).
- Execution outcome and any partial fills.
- Error codes with human‑readable explanations.
How can users trust the timeline’s accuracy?
Trust comes from transparency about data provenance and error handling. The timeline should surface the original market data timestamp and any warnings about data quality. When an order times out, the UI must indicate that the outcome is still pending rather than assuming failure.
- Show data source and freshness for each price used.
- Mark timeout events with a distinct icon and note that reconciliation is required.
- Link to detailed logs for any error code via a tooltip or modal.
How should limits and policies be visualized?
Owner‑signed limits such as order size, daily notional, or loss caps are central to risk control. The timeline should embed a small badge next to each order indicating which limit was evaluated and whether it passed. If a limit blocks an order, the entry must explain which policy triggered the block.
- Badge: "Size ≤ 10 k USD" - green if passed, red if blocked.
- Badge: "Daily Notional ≤ 100 k USD" - updated after each successful order.
- Tooltip with the exact policy field and owner‑signed value.
What role does reconciliation play in the timeline?
Because a timeout does not prove an order failed, the system must reconcile the on‑chain or venue state after each action. The timeline should include a reconciliation step that confirms the intended state matches the actual state, and flag any mismatches for review.
- Post‑order reconciliation entry with status "Confirmed" or "Mismatch".
- Link to a detailed position view for mismatched entries.
- Prompt for owner review when a mismatch is detected.
How can users intervene safely?
An emergency stop button can revoke the agent’s key, halting further automated actions. The timeline must record the stop event and note that existing positions remain open until the owner explicitly closes them. This separation prevents accidental liquidation while still cutting off new risk.
- Stop event entry with timestamp and revocation status.
- Reminder that withdrawals require a separate owner‑signed intent.
- Option to open a manual closure workflow from the timeline.
What visual cues improve usability?
Color coding, icons, and consistent layout reduce cognitive load. Use green for successful actions, amber for warnings (e.g., data freshness issues), and red for errors or limit violations. Group related entries (order → reconciliation) so users can follow the full lifecycle at a glance.
- Green check for filled orders.
- Amber clock for pending timeouts.
- Red exclamation for limit failures or errors.
- Collapsible sections for each trade cycle.
A transparent timeline is not just a log; it is a safety net that lets owners verify every automated decision and intervene when needed.
For deeper guidance on building safe agent controls, see What is agentic trading?, Why Positions Must Be Reconciled After Every Agent Order, and How to run an AI trading agent with real‑money controls.
Frequently asked questions
Precise timestamps let users correlate actions with market moves and verify that data used was current, which is essential for assessing execution quality.
Review the detailed position view linked in the mismatch entry, confirm the on‑chain state, and decide whether to adjust the position or investigate a possible error.
No. The stop revokes the agent’s key to prevent new orders, but existing positions require a separate owner‑authorized action to close or modify.
Reconciliation should happen after every order, including partial fills and timeouts, to ensure the recorded state matches the venue’s actual state.
Sources and verification
Product claims in this article were checked against these first-party references. Runtime status remains authoritative for current availability.
- Felix documentationfirst party
- Felix machine referencefirst party
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