generated: 2025-12-05

System Auto: last updated on: 2025-12-05 21:37:15

Session 31: Memory Agent Skill & Search Fix

Date: 2025-12-05 | Agent: Hephaestus (Builder)

Quick Reference

Identity

• Agent: Hephaestus (Builder)
• Mission: Agent Memory ETL Pipeline
• Spec: @docs/specs/TRD-ETL-v2.md
• Schema: @docs/specs/memory_db_schema_v3.sql (AUTHORITATIVE)

Status

Completed This Session

1. Dogfood Complete

Ingested updated docs into memory:

• Concepts: 60,446 -> 62,428 (+1,982)
• Embeddings: 59,707 -> 60,279 (+572)
• Coverage: 96.6% (new concepts pending embedding)

2. Memory Agent Skill Created

Created .claude/skills/memory-agent/SKILL.md - a Claude Code Skill that:

• Implements the ReasoningBank CLOSED loop pattern
• Is model-invoked (Claude decides when to use it)
• Instructs on RETRIEVE -> INJECT -> EXECUTE -> EXTRACT flow

Key innovation: Using Claude Code's native Skills system instead of building a wrapper.

3. Critical Bug Fixes

Fix A: Similarity Threshold Too Strict

File: haios_etl/retrieval.py:160 Change: Threshold 0.8 -> 0.6 Reason: Per Session 30 recommendation, 0.8 was too strict for experiential learning

Fix B: Search Missing 99% of Content

File: haios_etl/database.py:285-351 Problem: search_memories() only queried 572 artifact embeddings, ignoring 59,707 concept embeddings Fix: Added UNION ALL to search both artifact AND concept embeddings

-- Now searches BOTH (was only artifacts)
SELECT ... FROM embeddings e JOIN artifacts a ...
UNION ALL
SELECT ... FROM embeddings e JOIN concepts c ...

Verification: Direct Python test confirms fix works. MCP server requires restart for changes to take effect.

Key Discovery: Search Was Broken

The memory search was essentially non-functional because:

1. Artifacts = 572 file-level entries
2. Concepts = 62,428 content-level entries (where knowledge lives)
3. Search only looked at artifacts (0.9% of content)

This explains why memory_search_with_experience always returned empty results despite having 60k+ embeddings.

Architecture Insight: Skills vs Plugins

Memory Agent is a Skill because Claude should autonomously decide when to retrieve context or extract learnings.

Pending

1. MCP Server Restart - Required for search fixes to take effect
2. Remaining Embeddings - 2,149 concepts need embeddings (96.6% -> 100%)
3. Test Memory Search - Verify fix works after restart

Handoff Notes

To verify fixes after MCP restart:

memory_search_with_experience(query="HAIOS architecture", space_id="dev_copilot")

Should return concept results, not empty.

HANDOFF STATUS: Prototype complete, awaiting MCP restart for verification