Edge Signal Aggregator

Overview

Combine outputs from multiple upstream edge-finding skills into a single weighted conviction dashboard. This skill applies configurable signal weights, deduplicates overlapping themes, flags contradictions between skills, and ranks composite edge ideas by aggregate confidence score. The result is a prioritized edge shortlist with provenance links to each contributing skill.

When to Use

• After running multiple edge-finding skills and wanting a unified view
• When consolidating signals from edge-candidate-agent, theme-detector, sector-analyst, and institutional-flow-tracker
• Before making portfolio allocation decisions based on multiple signal sources
• To identify contradictions between different analysis approaches
• When prioritizing which edge ideas deserve deeper research

Prerequisites

• Python 3.9+
• No API keys required (processes local JSON/YAML files from other skills)
• Dependencies: pyyaml (standard in most environments)

Workflow

Step 1: Gather Upstream Skill Outputs

Collect output files from the upstream skills you want to aggregate:

• reports/edge_candidate_*.json from edge-candidate-agent
• reports/edge_concepts_*.yaml from edge-concept-synthesizer
• reports/theme_detector_*.json from theme-detector
• reports/sector_analyst_*.json from sector-analyst
• reports/institutional_flow_*.json from institutional-flow-tracker
• reports/edge_hints_*.yaml from edge-hint-extractor

Step 2: Run Signal Aggregation

Execute the aggregator script with paths to upstream outputs:

python3 skills/edge-signal-aggregator/scripts/aggregate_signals.py \
  --edge-candidates reports/edge_candidate_agent_*.json \
  --edge-concepts reports/edge_concepts_*.yaml \
  --themes reports/theme_detector_*.json \
  --sectors reports/sector_analyst_*.json \
  --institutional reports/institutional_flow_*.json \
  --hints reports/edge_hints_*.yaml \
  --output-dir reports/