Context Loader

Pre-fetches relevant memories to prime context before working on a task or topic.

When to use

• Session start (auto-triggered by the extension's before_agent_start event)
• User starts work on a specific topic or area
• User says "what do we know about X" or "context for X"

Steps

1. Extract topics from current message/task. Identify: subject areas, people mentioned, project names, goal references.

2. Run 2-4 parallel searches using mem0_memory tool with action="search" and different query angles:

   Query angle	Purpose
   Topic/subject name	Relevant decisions and preferences
   People mentioned	Relationship context
   Project/goal references	Progress and background
   Broad context	Catch-all for anything relevant

3. Deduplicate results by memory ID across all search responses.

4. Output compact context block (max 10 memories):

context-loader: loaded <N> memories for "<task summary>"
  - [decisions] <content> [mem0:<short_id>]
  - [preferences] <content> [mem0:<short_id>]
  - [lessons] <content> [mem0:<short_id>]

5. If zero results: output nothing. Don't announce empty context.

Constraints

• Read-only — never modify or delete memories
• Max 10 memories returned (most relevant only)
• Silent on empty — only surfaces findings if relevant context exists
• Skip memories already visible in current session context