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Dorpeer95
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edge-signal-aggregator

Aggregate outputs from multiple edge-finding skills into a weighted conviction dashboard.

Updated Mar 1, 2026
Search Tags:#aggregation#provenance#signals#scoring#deduplication#edge#conviction
One-click install
npx skills add https://github.com/Dorpeer95/stocks-trading --skill edge-signal-aggregator-dorpeer95
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: edge-signal-aggregator
Source: https://github.com/Dorpeer95/stocks-trading/tree/main/.claude/skills/edge-signal-aggregator
Command: npx skills add https://github.com/Dorpeer95/stocks-trading --skill edge-signal-aggregator-dorpeer95

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pyyaml, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

Aggregate and rank signals from multiple edge-finding skills into a single, prioritized conviction dashboard, reducing noise and enabling faster decision-making.

Core Features & Use Cases

  • Weighted aggregation across edge-candidate-agent, edge-concept-synthesizer, theme-detector, sector-analyst, institutional-flow-tracker, and edge-hint-extractor.
  • Deduplication and contradiction detection with provenance links to sources.
  • Quick-start scenario: feed outputs from upstream skills and generate a ranked edge shortlist for review.

Quick Start

Use the edge-signal-aggregator to combine outputs from your upstream edge-finding skills and generate a concise ranked dashboard.

Frequently Asked Questions about edge-signal-aggregator

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I aggregate signals from multiple edge-finding tools into a single ranked dashboard?▼

You can aggregate signals from multiple edge-finding tools by feeding their outputs into an aggregator that applies configurable weights, deduplication, and contradiction detection to produce a single ranked conviction dashboard.

What is provenance-aware signal scoring and how does it help rank edge signals?▼

Provenance-aware signal scoring ranks edge signals by tracking their original sources, applying configurable weights and recency adjustments, and flagging contradictions to ensure high-confidence ranking with source references.

How do I consolidate duplicate edge signals and resolve contradictions from different sources?▼

To consolidate duplicate edge signals and resolve contradictions, the aggregator applies provenance tracking and merge logs to deduplicate overlapping outputs while flagging contradictions for transparent, source-referenced decision-making.

Can I use YAML to configure weights and recency adjustments for edge signal aggregation?▼

Yes, you can use YAML to configure weights and recency adjustments for edge signal aggregation, allowing you to prioritize specific upstream sources and adjust signal impact based on recency within the conviction dashboard.

Does edge signal aggregation work with outputs from theme detection and institutional flow tracking?▼

Yes, edge signal aggregation works with outputs from theme-detector, institutional-flow-tracker, edge-candidate-agent, edge-concept-synthesizer, sector-analyst, and edge-hint-extractor by consolidating them into a weighted conviction dashboard.

What are the limitations of aggregating edge signals from multiple upstream skills?▼

The main limitation is dependency on upstream skill outputs; the aggregator cannot generate new edge signals independently, it only consolidates, deduplicates, and ranks existing signals using configurable weights and provenance tracking.

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