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Searches and injects relevant memories into context before starting work on a task. Use when beginning a new task, switching context, or when project history, past decisions, or coding conventions need to be loaded.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Searches and injects relevant memories into context before starting work on a task. Use when beginning a new task, switching context, or when project history, past decisions, or coding conventions 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 Use when removing outdated decisions, incorrect memories, sensitive data, or cleaning up after experiments. Also handles undo of recent additions.
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 architecture decisions, security constraints, or immutable team conventions.
Stores a memory verbatim from user input with appropriate type classification and metadata. Use when the user says remember this, save this, store this, note that, or explicitly asks to record a decision, preference, convention, or learning.
Views or changes the default memory scope (project, session, or global) used when saving and searching memories. Use when the user wants to control whether memories are scoped to this repo, this run, or shared across all their projects.
| name | context-loader |
| description | Searches and injects relevant memories into context before starting work on a task. Use when beginning a new task, switching context, or when project history, past decisions, or coding conventions need to be loaded. |
Pre-fetches relevant memories to prime context before working on a task.
Extract topics from current message/task. Identify: file paths, module names, feature areas, error patterns.
Run 2-4 parallel search_memories calls with different angles:
| Query angle | Filter | Purpose |
|---|---|---|
| Feature/module name | {"AND": [{"user_id": "<id>"}, {"app_id": "<pid>"}, {"metadata": {"type": "decision"}}]} | Architecture decisions |
| File paths mentioned | {"AND": [{"user_id": "<id>"}, {"app_id": "<pid>"}, {"metadata": {"type": "convention"}}]} | Coding patterns |
| Error keywords (if any) | {"AND": [{"user_id": "<id>"}, {"app_id": "<pid>"}, {"metadata": {"type": "anti_pattern"}}]} | Known pitfalls |
| Broad project context | {"AND": [{"user_id": "<id>"}, {"app_id": "<pid>"}]} | Catch-all |
Deduplicate results by memory ID across all search responses.
Output compact context block (max 10 memories):
context-loader: loaded <N> memories for "<task summary>"
- [decision] <content> [mem0:<short_id>]
- [convention] <content> [mem0:<short_id>]
- [anti_pattern] <content> [mem0:<short_id>]