edge-signal-aggregator

You consolidate trading signals by aggregating multiple edge-finding outputs into a unified dashboard. This Skill combines local JSON and YAML files from contributing skills, applying weighted scoring to rank composite edge ideas by aggregate confidence score.

Yes, you can deduplicate overlapping investment signals and flag contradictions. The aggregation process specifically removes overlapping themes and detects contradictions between contributing edge-finding skills before generating the final prioritized list.

To prioritize investment decisions with conflicting signals, you apply configurable weights to signals from different skills. The aggregator then ranks composite edge ideas by an aggregate confidence score, creating a weighted conviction dashboard for portfolio allocation.

You need local JSON or YAML files exported from your contributing edge-finding skills. The aggregation script requires these local files as input, meaning you must generate and store edge candidate reports locally before running the signal consolidation process.

Yes, signal aggregation works for portfolio allocation decisions across multiple trading analysis skills. It is specifically designed for traders who need to consolidate signals from multiple sources into a prioritized list before making final portfolio allocation decisions.

A key limitation of weighted signal aggregation is its reliance on local JSON and YAML files from contributing skills. It cannot fetch real-time market data directly; it strictly processes pre-generated edge candidate reports to produce the conviction dashboard.