From tradermonty-claude-trading-skills
Aggregates and ranks outputs from edge-finding skills like edge-candidate-agent and theme-detector into a prioritized conviction dashboard with weighted scoring, deduplication, and contradiction detection. Use to unify signals before deeper analysis.
npx claudepluginhub joshuarweaver/cascade-business-ops --plugin tradermonty-claude-trading-skillsThis skill uses the workspace's default tool permissions.
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.
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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.
pyyaml (standard in most environments)Collect output files from the upstream skills you want to aggregate:
reports/edge_candidate_*.json from edge-candidate-agentreports/edge_concepts_*.yaml from edge-concept-synthesizerreports/theme_detector_*.json from theme-detectorreports/sector_analyst_*.json from sector-analystreports/institutional_flow_*.json from institutional-flow-trackerreports/edge_hints_*.yaml from edge-hint-extractorExecute 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/
Open the generated report to review:
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/
{
"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
}
]
}
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.jsonedge_signal_aggregator_YYYY-MM-DD_HHMMSS.mdscripts/aggregate_signals.py -- Main aggregation script with CLI interfacereferences/signal-weighting-framework.md -- Rationale for default weights and scoring methodologyassets/default_weights.yaml -- Default skill weights configuration