narrative-convergence

Aggregate skill outputs and memory logs to rank convergent write signals.

Updated Jun 2, 2026

Search Tags:#narrative #signals #convergence #cross-skill #memory-logs #write-angle

Ready to run

npx skills add https://github.com/Atrium-Hermes/atrium-lighthouse --skill narrative-convergence

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: narrative-convergence
Source: https://github.com/Atrium-Hermes/atrium-lighthouse/tree/main/skills/narrative-convergence
Command: npx skills add https://github.com/Atrium-Hermes/atrium-lighthouse --skill narrative-convergence

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Cross-skill convergence signals across independent skills reveal overlooked trends. This skill automatically surfaces high-confidence write opportunities when multiple skills flag the same entity within 48 hours.

Core Features & Use Cases

Cross-skill signal detection: aggregates outputs from multiple skills and memory logs to identify convergent entities and themes.
Scoring & ranking: evaluates how many skills and categories converge and prioritizes top signals for write opportunities.
Write opportunity generation: suggests write angles and hooks with operator-friendly framing and keeps a traceable memory of signals.

Quick Start

Run the convergence scan to surface cross-skill signals and draft a write angle.

Frequently Asked Questions about narrative-convergence

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

FAQPage Schema

How do I detect cross-skill convergence signals from multiple memory logs?▼

Cross-skill convergence signals are detected by aggregating outputs from multiple skills and memory logs to identify when 3 or more independent skills flag the same entity or theme within a 48-hour window.

What is cross-skill signal aggregation and when do I need it?▼

Cross-skill signal aggregation is the process of compiling outputs across independent skills to reveal overlooked trends. You need it to surface high-confidence write opportunities when multiple skills flag the same entity.

How do I generate write angles from aggregated convergence signals?▼

Generate write angles by running a convergence scan that scores and ranks convergent entities, producing a prioritized list of top signals with operator-friendly framing, hooks, and memory-update artifacts.

Can I surface write opportunities if only two independent skills flag the same entity?▼

No, surfacing high-signal write opportunities requires 3 or more independent skills to flag the same entity or theme within 48 hours to ensure high confidence and reduce false positives.

Does cross-skill convergence scoring require specific dependencies to rank signals?▼

No specific dependencies are required. Convergence scoring evaluates how many independent skills and categories converge on a single entity to prioritize and rank the top signals for write opportunities.

Why are cross-skill convergence signals not appearing in my memory logs?▼

Convergence signals will not appear unless the 48-hour threshold and 3-skill minimum are met. The system updates memory with convergence results only after successfully identifying these strict overlaps.