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/ Optional: Use a custom weights configuration: python3 skills/edge-signal-aggregator/scripts/aggregate_signals.py \ --edge-candidates reports/edge_candidate_agent_.json \ --weights-config skills/edge-signal-aggregator/assets/custom_weights.yaml \ --output-dir reports/ Step 3: Review Aggregated Dashboard Open the generated report to review: Ranked Edge Ideas - Sorted by composite conviction score Signal Provenance - Which skills contributed to each idea Contradictions - Conflicting signals flagged for manual review Deduplication Log - Merged overlapping themes Step 4: Act on High-Conviction Signals Filter the shortlist by minimum conviction threshold: python3 skills/edge-signal-aggregator/scripts/aggregate_signals.py \ --edge-candidates reports/edge_candidate_agent_.json \ --min-conviction 0.7 \ --output-dir reports/ Output Format JSON Report { "schema_version" : "1.0" , "generated_at" : "2026-03-02T07:00:00Z" , "config" : { "weights" : { "edge_candidate_agent" : 0.25 , "edge_concept_synthesizer" : 0.20 , "theme_detector" : 0.15 , "sector_analyst" : 0.15 , "institutional_flow_tracker" : 0.15 , "edge_hint_extractor" : 0.10 } , "min_conviction" : 0.5 , "dedup_similarity_threshold" : 0.8 } , "summary" : { "total_input_signals" : 42 , "unique_signals_after_dedup" : 28 , "contradictions_found" : 3 , "signals_above_threshold" : 12 } , "ranked_signals" : [ { "rank" : 1 , "signal_id" : "sig_001" , "title" : "AI Infrastructure Capex Acceleration" , "composite_score" : 0.87 , "contributing_skills" : [ { "skill" : "edge_candidate_agent" , "signal_ref" : "ticket_2026-03-01_001" , "raw_score" : 0.92 , "weighted_contribution" : 0.23 } , { "skill" : "theme_detector" , "signal_ref" : "theme_ai_infra" , "raw_score" : 0.85 , "weighted_contribution" : 0.13 } ] , "tickers" : [ "NVDA" , "AMD" , "AVGO" ] , "direction" : "LONG" , "time_horizon" : "3-6 months" , "confidence_breakdown" : { "multi_skill_agreement" : 0.30 , "signal_strength" : 0.35 , "recency" : 0.22 } } ] , "contradictions" : [ { "contradiction_id" : "contra_001" , "description" : "Conflicting sector view on Energy" , "skill_a" : { "skill" : "sector_analyst" , "signal" : "Energy sector bearish rotation" , "direction" : "SHORT" } , "skill_b" : { "skill" : "institutional_flow_tracker" , "signal" : "Heavy institutional buying in XLE" , "direction" : "LONG" } , "resolution_hint" : "Check timeframe mismatch (short-term vs long-term)" } ] , "deduplication_log" : [ { "merged_into" : "sig_001" , "duplicates_removed" : [ "theme_detector:ai_compute" , "edge_hints:datacenter_demand" ] , "similarity_score" : 0.92 } ] } Markdown Report The markdown report provides a human-readable dashboard:
Edge Signal Aggregator Dashboard ** Generated: ** 2026-03-02 07:00 UTC
Summary
Total Input Signals: 42
Unique After Dedup: 28
Contradictions: 3
High Conviction (>0.7): 12
Top 10 Edge Ideas by Conviction
1. AI Infrastructure Capex Acceleration (Score: 0.87)
** Tickers: ** NVDA, AMD, AVGO - ** Direction: ** LONG | ** Horizon: ** 3-6 months - ** Contributing Skills: ** - edge-candidate-agent: 0.92 (ticket_2026-03-01_001) - theme-detector: 0.85 (theme_ai_infra) - ** Confidence Breakdown: ** Agreement 0.30 | Strength 0.35 | Recency 0.22 ...
Contradictions Requiring Review
Energy Sector Conflict
** sector-analyst: ** Bearish rotation (SHORT) - ** institutional-flow-tracker: ** Heavy buying XLE (LONG) - ** Hint: ** Check timeframe mismatch
Deduplication Summary
14 signals merged into 8 unique themes
Average similarity of merged signals: 0.89 Reports are saved to reports/ with filenames: edge_signal_aggregator_YYYY-MM-DD_HHMMSS.json edge_signal_aggregator_YYYY-MM-DD_HHMMSS.md Resources scripts/aggregate_signals.py -- Main aggregation script with CLI interface references/signal-weighting-framework.md -- Rationale for default weights and scoring methodology assets/default_weights.yaml -- Default skill weights configuration Key Principles Provenance Tracking -- Every aggregated signal links back to its source skill and original reference Contradiction Transparency -- Conflicting signals are flagged, not hidden, to enable informed decisions Configurable Weights -- Default weights reflect typical reliability but can be customized per user Deduplication Without Loss -- Merged signals retain references to all original sources Actionable Output -- Ranked list with clear tickers, direction, and time horizon for each idea