Optimize agent dashboard trade grouping

[taherdhanera]

Summary

• pre-group dashboard trades by agent_id once per trades update
• pass each agent card its precomputed trade list instead of filtering the full trade array during every render
• keep the change scoped to the agents dashboard performance path

Performance impact

Before this change, the agent grid called trades.filter((t) => t.agent_id === a.id) inside agents.map(...). That makes the render path do repeated full-array scans (agents * trades) and creates a new trade array for every card on every render, which can force each sparkline to rebuild chart data unnecessarily.

After this change, the page builds a memoized tradesByAgent map in one pass whenever trades changes. Rendering agent cards becomes a constant-time lookup per agent, reducing repeated work as the number of agents or closed trades grows.

Benchmark evidence

Synthetic dashboard-sized benchmark with checksum equality:

Dataset	Old path	New path	Speedup
50 agents / 10,000 trades / 100 render passes	1224.226ms	66.403ms	18.44x
100 agents / 25,000 trades / 50 render passes	1702.786ms	63.644ms	26.75x
200 agents / 50,000 trades / 20 render passes	1942.593ms	55.688ms	34.88x

This targets the frontend agents dashboard render bottleneck. Other same-issue bounty PRs cover adjacent areas such as backend indicators, chart downsampling, or API/network paths; they do not replace this dashboard trade-grouping optimization.

Validation

• git diff --check
• Syntax-oriented TypeScript parse command was run against the changed TSX file; it reached dependency-resolution errors because the checkout has no node_modules, but did not report syntax errors in the changed block.

Refs #2

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