القائمة
Checkpoint episodes and create handoff packs for multi-agent session continuity
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Configure, test, benchmark, and manage embedding providers for semantic search and vector operations
Create and traverse typed relationships between episodes for dependency tracking and knowledge graphs
Manage episode tags for organization, filtering, and retrieval across the memory system
Generate task playbooks and explain patterns using learned strategies from episodic memory
Record and analyze recommendation sessions and feedback to drive the self-learning loop
Use and troubleshoot the Memory MCP server for episodic memory retrieval and pattern analysis. Use when working with MCP server tools, validating the MCP implementation, or debugging MCP server issues.
| name | checkpoint-handoff |
| description | Checkpoint episodes and create handoff packs for multi-agent session continuity |
| Command | Purpose |
|---|---|
do-memory-cli episode checkpoint <EPISODE_ID> | Create checkpoint of current episode state |
do-memory-cli episode checkpoint <EPISODE_ID> --note "reason" | Checkpoint with annotation |
| Tool | Parameters | Purpose |
|---|---|---|
checkpoint_episode | episode_id, note (optional) | Save episode state snapshot |
get_handoff_pack | episode_id | Generate complete context pack for handoff |
resume_from_handoff | handoff_pack | Resume episode from a handoff pack |
Agent A: Working on episode...
1. checkpoint_episode(episode_id, note: "completed API design")
2. get_handoff_pack(episode_id)
→ Returns: { episode state, steps, patterns applied, context }
Agent B: Resuming work...
1. resume_from_handoff(handoff_pack)
→ Restores context, continues episode
1. Agent hits context limit or session ends
2. checkpoint_episode(episode_id, note: "context limit reached")
3. New session starts
4. get_handoff_pack(episode_id)
5. resume_from_handoff(pack)
6. Continue adding steps to the same episode
The system automatically creates checkpoints when an agent abstains (decides not to act). These are queryable via list_abstention_checkpoints() for analyzing decision patterns.