episodic-recall

name	episodic-recall
description	Queries episodic memory to find past experiences relevant to the current context. Use when any agent needs to recall past decisions, outcomes, or patterns from Jarvis's experience history. Currently a stub — full implementation pending Phase 2 Mem0 integration. Falls back to recall_similar_decisions tool.
compatibility	google-adk
metadata	{"scope":"shared","phase":2,"status":"stub","triggers":["needing context from past experiences","looking for similar past decisions or outcomes","connecting current situation to historical patterns"],"requires_tools":["recall_similar_decisions"]}

Episodic Recall (Phase 2 Stub)

STATUS: STUB — This skill documents the Phase 2 episodic memory protocol. The full implementation requires recall_episodic tool backed by Mem0 + ChromaDB, which will be available in Phase 2. Until then, use the fallback below.

What This Will Do (Phase 2)

When fully implemented, this skill enables natural-language queries against Jarvis's episodic memory — all past journal entries, decisions, outcomes, and learnings indexed for hybrid semantic + keyword retrieval.

Phase 2 Protocol:

1. Agent formulates a natural language query about past experience
2. Query is sent to Mem0 (hybrid semantic + BM25 retrieval)
3. Top-k results are returned with metadata (date, section, cognitive_load_score)
4. Results are formatted as ActMem-style reasoning chains:

   Context: <what was happening when this was stored>
   Implication: <what this means for the current situation>
   Confidence: <retrieval confidence score>
   

5. Agent uses these to inform current decision-making

Current Fallback

Until Phase 2 is available, use recall_similar_decisions tool instead:

recall_similar_decisions(situation="<describe the current situation>")

This searches the Judge's accumulated beliefs (flat JSON) for relevant entries. It's less powerful than the Phase 2 episodic memory but provides basic recall.

Limitations of fallback:

• Only searches beliefs, not full journal history
• No semantic search (exact/substring match only)
• No confidence scoring
• No temporal context (doesn't know WHEN beliefs were formed)

How to Use Now

1. Describe the current situation or question
2. Call recall_similar_decisions with that description
3. Review returned beliefs for relevance
4. Note: results will be much richer after Phase 2 migration

Phase 2 Prerequisites

• mem0ai package installed
• chromadb running (embedded mode)
• Journal entries indexed via EpisodicMemory.index_journal_entry()
• recall_episodic tool registered in agent tools