Agent skill · writing content · mem0ai
context-loader
Searches and injects relevant memories into context before starting work on a task or topic. Use when beginning a new task, switching context, or when past decisions, preferences, or knowledge need to be loaded.
Why this skill is useful
Adds a structured method for retrieving and injecting relevant contextual memories that the AI wouldn't generate on its own.
What it needs
About 1k tokens when loaded. Last updated 2026-08-06. 62,725 stars on the source repository.
What this skill does
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 beforeagentstart 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 mem0memory 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): 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
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills mem0ai/context-loader--d6dc84