majiayu000/claude-arsenal
xiaohongshu
xiaohongshu
286 148
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Episodic Archiver
episodic-archiver
Episodic Memory Archiver. Stores full conversation transcripts with embeddings and analysis into ArangoDB. Tracks UNRESOLVED sessions for reflection.
SKILL.md
Full skill instructions
Episodic Archiver
Analyzes conversation transcripts, embeds them for search, categorizes turns, and tracks unresolved sessions for later reflection.
Commands
# Archive a conversation transcript
./run.sh archive transcript.json
# List unresolved sessions (for reflection)
./run.sh list-unresolved
# Mark a session as resolved after follow-up
./run.sh resolve <session_id>
Unresolved Session Tracking
When archiving, the skill analyzes if the session was resolved:
| Condition | Result |
|---|---|
| Session ends with error | Unresolved |
| Session ends with unanswered question | Unresolved |
| Errors without following solutions | Unresolved |
| Tasks without completion | Unresolved |
Unresolved sessions are stored in unresolved_sessions collection for reflection.
Integration with /learn
# Reflect on past failures to find what to learn
/learn --from-gaps --scope horus_lore
# This queries:
# 1. unresolved_sessions (high priority)
# 2. agent_conversations (errors, questions)
# 3. Skill logs (failures)
The Reflection Loop
Session ends → Archive → Detect unresolved → Store gap
↓
/learn --from-gaps
↓
Curiosity targets
↓
/dogpile → /learn
↓
Knowledge acquired
↓
./run.sh resolve <session>
Storage
Collections:
agent_conversations- Individual turns with embeddingsunresolved_sessions- Sessions needing follow-up
Turn categories: Task, Question, Solution, Error, Chat, Meta
Input Format
{
"session_id": "task_123",
"messages": [
{"from": "User", "content": "Fix the bug in auth", "timestamp": 1234567890},
{"from": "Agent", "content": "Looking at auth.py...", "timestamp": 1234567891}
]
}
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