memory-router

name	memory-router
description	Route tasks in the ai-memory project and load only the minimum required memory context. Always use this skill when user asks about ai-memory architecture, inject modes, copilot-instructions redesign, project memory lookup, learn pipeline behavior, or when a subagent should avoid broad file reads.
metadata	{"keywords":["routing","minimal context","inject modes","copilot instructions"],"triggers":["how should we route this task","inject strategy","copilot instructions redesign","最小化读取路径"]}

Memory Router

Use this skill to avoid overloading context while keeping project understanding accurate.

Goal

• Identify task type quickly.
• Load minimum context first.
• Escalate to deeper files only when needed.

Task Classification

• First-turn project understanding:
  • Read .github/skills/memory-project-context/SKILL.md first.
• Inject and instruction design:
  • Read ai-memory and .github/copilot-instructions.md first.
• Core architecture:
  • Read docs/core-idea.md first, then ai-memory.
• Learn pipeline:
  • Read lib/learn.sh and ai-memory config/inject branches.
• Project status:
  • Read note.md.

Retrieval Ladder

1. ai-memory capability
2. .github/skills/memory-project-context/SKILL.md (project semantic index)
3. ai-memory context
4. ai-memory project (only if project-specific)
5. Open exact file sections for implementation details

Response Contract

• Start with direct answer in 1-3 lines.
• Then list only the files actually needed.
• For subagent tasks, state a concrete read plan before opening files.
• If proposing edits, keep diff surface small and mention validation steps.

Token Discipline

• Do not paste large snapshots unless asked.
• Prefer summaries over full file dumps.
• For VS Code instructions, keep the main file lightweight and route to project summary/skills.