What problem does it solve?
Executives and operators accumulate saves, highlights, notes, and decisions across many tools but rarely turn that trail into clear decisions, often confusing attention (bookmarks) with conviction (applied work). This Skill separates weak attention signals from strong conviction evidence and converts the trail into decision briefs, experiments, and validated recommendations.
Core Features & Use Cases
- Attention vs. Conviction Scoring: Applies an 8-level signal-strength ladder so saves are never treated as endorsements, and every claim links back to primary source IDs with no recursive evidence.
- Seven Capability Modules: Attention Drift, Pre-Decision Oracle, Contradiction/Decision Court, Bookmark-to-Build, Founder-IP Recombination, Service-Offer Arbitrage, and Content Negative-Space.
- Quality Gate and Privacy Controls: A configurable expert panel scores outputs against a default 90/100 threshold, while private inferred beliefs stay labeled, confidence-rated, and excluded from shareable output.
- Use Case: Run a weekly strategic signal review that surfaces the strongest decision-relevant pattern, one contradiction to resolve, one bounded build or experiment, and one content gap, all with source lineage.
Quick Start
Ask your AI agent to run my weekly strategic signal review, keeping attention separate from conviction and citing primary sources for every claim.
