signal-detector

Monitor messages for original thinking and entity mentions as a background sub-agent.

Updated Aug 27, 2026
One-click install
npx skills add https://github.com/mscully4/franklin --skill signal-detector-mscully4
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: signal-detector
Source: https://github.com/mscully4/franklin/tree/main/.claude/skills/signal-detector
Command: npx skills add https://github.com/mscully4/franklin --skill signal-detector-mscully4

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill enables continuous monitoring and capture of original thinking and entity mentions from inbound messages, ensuring valuable insights and data are not missed.

Core Features & Use Cases

  • Ambient Signal Capture: Always-on detection of original thinking and entity mentions in inbound messages.
  • Parallel Execution: Spawns as a sub-agent to ensure it never blocks the main response.
  • Data Collection: Captures and logs user ideas and entity mentions for later analysis.
  • Use Case: For a team brainstorming session, the Skill can capture innovative ideas and references to key players or companies, enriching the team's knowledge base over time.

Quick Start

Use the signal-detector skill to capture ambient signals from all incoming messages.

Frequently Asked Questions about signal-detector

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

FAQPage Schema
How do I capture ambient signals and entity mentions from inbound messages without blocking the main response?

Ambient signal capture works by spawning a background sub-agent that continuously monitors inbound messages for original thinking and entity mentions. This parallel execution model ensures the main response is never blocked while continuously enriching your knowledge base.

What is ambient signal capture and how does it support continuous learning?

Ambient signal capture is the always-on detection of original thinking and entity mentions within message streams. It supports continuous learning by logging these insights and data points in the background, enabling ongoing knowledge base expansion without interrupting active workflows.

Can I use a background sub-agent for non-blocking message analysis during a team brainstorming session?

Yes, you can use a background sub-agent for non-blocking message analysis during brainstorming sessions. It operates in parallel to capture innovative ideas and references to key players or companies, actively enriching the team's knowledge base over time without disrupting the main conversation.

How do I enrich my knowledge base by detecting entities in message streams?

You enrich your knowledge base by applying always-on entity detection to inbound message streams. The system automatically captures and logs user ideas alongside specific entity mentions for later analysis, ensuring valuable references and insights are continuously collected and stored.

Does parallel execution for insight capture affect the performance of my main application?

Parallel execution for insight capture does not affect main application performance because the monitoring process spawns as an isolated sub-agent. This non-blocking execution model separates the data collection and entity detection tasks, ensuring the primary response remains fully responsive.