Episodic Memory Archiver. Stores full conversation transcripts with embeddings and analysis into ArangoDB. Use this to save the "User Story" or "Chain of Thought".
Installs into .claude/skills of the current project.
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---
name: episodic-archiver
description: >
Episodic Memory Archiver. Stores full conversation transcripts with embeddings
and analysis into ArangoDB. Use this to save the "User Story" or "Chain of Thought".
allowed-tools: Bash
triggers:
- archive conversation
- save episode
- store transcript
- remember this conversation
metadata:
short-description: Analyzes and stores episodic conversation memory
---
# Episodic Archiver
This skill analyzes full conversation transcripts, embeds them for search, and categorizes turns.
## Usage
```bash
# Save a JSON transcript to episodic memory
.agents/skills/episodic-archiver/run.sh archive <transcript.json>
```
## Input Format
The JSON file should be a list of messages or an object with a `messages` list:
```json
{
"session_id": "task_123",
"messages": [
{
"from": "Coordinator",
"to": "Worker",
"message": "Please fix the bug...",
"timestamp": 1234567890
},
...
]
}
```
## Storage
Data is stored in ArangoDB collection `agent_conversations` with:
- `embedding`: Vector representation (768d)
- `category`: LLM-derived tag (Task, Question, Solution, etc.)
## Prerequisites
- ArangoDB credentials in `.env` (e.g., `ARANGO_URL`, `ARANGO_DB`, `ARANGO_USER`, `ARANGO_PASS`).
- **Embedding service** running (recommended): `EMBEDDING_SERVICE_URL=http://127.0.0.1:8602`
- Falls back to local `graph_memory` embedding model if service unavailable.
- Optional: `CHUTES_API_KEY` or `OPENAI_API_KEY` (for categorization).
