/context-loader

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.

Context Loader

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

When to use

• Session start (invoke manually or auto-triggered by skill description matching)
• User starts work on a specific feature or file set
• Complex multi-step task begins
• User says "what do we know about X" or "context for X"

Steps

1. **Extract topics** from current message/task. Identify: file paths, module names, feature areas, error patterns.

2. **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 |

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>"
  - [decision] <content> [mem0:<short_id>]
  - [convention] <content> [mem0:<short_id>]
  - [anti_pattern] <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