signal-detector

Capture decisions, patterns, entity mentions, and insights from conversations into agent memory.

1|Updated Jan 26, 2026

Search Tags:#patterns #memory #conversation #agent-memory #entity-mentions #signal

Ready to run

npx skills add https://github.com/manastalukdar/ai-devstudio --skill signal-detector-manastalukdar

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: signal-detector
Source: https://github.com/manastalukdar/ai-devstudio/tree/main/skills/signal-detector
Command: npx skills add https://github.com/manastalukdar/ai-devstudio --skill signal-detector-manastalukdar

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

I run silently in the background on every session to capture signals worth remembering — architectural decisions, recurring patterns, entity mentions, and original insights — and write them to the appropriate agent memory file.

Core Features & Use Cases

Captures architectural decisions, recurring patterns, entity mentions, and original insights from conversations.
Routes signals to the correct agent memory location (code-reviewer, test-runner, security-auditor, etc.) based on context.
Supports compiled truth and timeline updates, with notability gating to ensure lasting, actionable memory.

Quick Start

Enable ambient signal capture so the detector runs in the background and writes signals to the agent memory.

Frequently Asked Questions about signal-detector

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

FAQPage Schema

How do I capture architectural decisions and recurring patterns from agent conversations automatically?▼

You can capture architectural decisions and recurring patterns by running an ambient signal detector in the background across sessions. It silently identifies these conversation signals and writes them to the appropriate agent memory file without blocking your main response.

What is ambient agent memory for conversation signals and how does it work?▼

Ambient agent memory is a background process that intercepts conversation signals like entity mentions and original insights. It operates silently across sessions, routing captured data to correct memory locations based on context to maintain compiled truth and timelines.

How do I route captured conversation insights to specific agent memory locations?▼

Routing conversation insights to specific agent memory locations happens automatically based on context. The detector identifies signals and directs them to the correct memory file, such as code-reviewer or security-auditor, satisfying memory-routing rules.

Can I use background signal capture to track entity mentions without interrupting the main workflow?▼

Yes, background signal capture tracks entity mentions without interrupting your main workflow. The detector operates ambiently across sessions, ensuring memory routing and notability gating occur silently without blocking the primary response.

How does notability gating work for agent memory updates?▼

Notability gating ensures agent memory updates remain lasting and actionable by evaluating captured conversation signals. It filters insights, architectural decisions, and patterns before writing them to memory, supporting compiled truth and timeline updates.

Best way to maintain compiled truth and timelines from conversation patterns?▼

The best way to maintain compiled truth and timelines is using an ambient memory detector to capture conversation patterns. It gates notability and routes signals to the correct memory location, ensuring accurate timeline updates without manual intervention.