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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.
Consolidates stored memories by merging duplicates, resolving contradictions, and pruning stale entries. Use when memory count is high, search results feel noisy or repetitive, or periodic cleanup is needed to maintain memory quality.
Deletes memories by search query or memory ID with confirmation before removal. Use when removing outdated information, incorrect memories, sensitive data, or cleaning up after experiments.
Pins or unpins a memory to protect it from pruning during dream consolidation. Use when a memory is critical and must never be removed, such as core preferences, important decisions, or immutable personal facts.
Stores a memory verbatim from user input with appropriate category classification. Use when the user says remember this, save this, store this, note that, or explicitly asks to record a preference, decision, goal, or lesson.
Searches memories and displays compact one-liner results, or looks up a specific memory by ID. Use for quick memory lookups, checking if something was recorded, resolving [mem0:id] citations, or browsing memories without full category detail.
Diagnoses Mem0 connectivity, API key validity, and memory read/write functionality. Use when memory operations fail, searches return empty, or to verify the plugin is working correctly.
| name | context-loader |
| description | 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. |
Pre-fetches relevant memories to prime context before working on a task or topic.
before_agent_start event)Extract topics from current message/task. Identify: subject areas, people mentioned, project names, goal references.
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 |
Deduplicate results by memory ID across all search responses.
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>]