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Ww Diagnose
ASecurityProblem diagnosis for World Weaver memory systems - identify root causes and suggest fixes
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- Added May 28, 2026
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[](https://www.skillsdirectory.com/skills/astoreyai-ww-diagnose)---
name: ww-diagnose
description: Problem diagnosis for World Weaver memory systems - identify root causes and suggest fixes
version: 1.0.0
allowed-tools: ['Bash', 'Read', 'Write', 'Grep', 'Glob']
---
# WW Diagnose Skill
Problem diagnosis for World Weaver memory systems - identify root causes and suggest fixes.
## Purpose
This skill provides diagnostic capabilities for:
1. **Learning Issues**: Why isn't learning improving?
2. **Memory Issues**: Why can't I find memories?
3. **Performance Issues**: Why is it slow?
4. **Integration Issues**: Why isn't MCP working?
5. **Consistency Issues**: Why is data corrupted?
## When to Use
Invoke this skill when:
- User reports "learning isn't working"
- User reports "can't find my memories"
- User reports "it's very slow"
- User reports "getting errors"
- User reports "data seems wrong"
## Diagnostic Decision Tree
### Symptom: Learning Not Improving
```
1. Check neuromodulators
→ Are DA/NE/ACh returning non-zero values?
→ Run: ww-bio-auditor
2. Check eligibility traces
→ Is decay happening correctly?
→ Run: ww-trace-debugger
3. Check weight updates
→ Is strengthen_relationship() implemented?
→ Is three-factor learning complete?
4. Check learning rates
→ Episodic LR >> Semantic LR?
→ CLS ratio correct?
```
### Symptom: Memory Not Found
```
1. Check storage
→ Was memory actually stored?
→ Query: mcp__ww-memory__recall_episodes(query="*", limit=5)
2. Check embeddings
→ Is vector index populated?
→ Query: Check Qdrant collection
3. Check retrieval
→ Is query embedding computed?
→ Is similarity threshold too high?
4. Check session
→ Is session ID correct?
→ Is there a session mismatch?
```
### Symptom: Slow Performance
```
1. Check database connections
→ Is Neo4j responding?
→ Is Qdrant responding?
2. Check query patterns
→ Are there N+1 queries?
→ Is there missing indexing?
3. Check memory usage
→ Is there unbounded growth?
→ Run: ww-leak-hunter
4. Check caching
→ Is cache being used?
→ Is cache invalidation correct?
→ Run: ww-cache-analyzer
```
### Symptom: Data Corruption
```
1. Check race conditions
→ Is there concurrent access?
→ Run: ww-race-hunter
2. Check cache coherence
→ Is stale data being served?
→ Run: ww-cache-analyzer
3. Check transaction integrity
→ Are writes atomic?
→ Is there rollback on failure?
4. Check type consistency
→ Are IDs consistent (str vs int)?
→ Are timestamps consistent?
```
## Diagnostic Commands
### Quick Health Check
```bash
# Check service health
curl http://localhost:7474 # Neo4j
curl http://localhost:6333/collections # Qdrant
# Check MCP server
ps aux | grep ww.mcp
# Check logs
tail -50 /tmp/ww-*.log
```
### Database Diagnostics
```python
# Neo4j query analysis
PROFILE MATCH (e:Episode) RETURN count(e)
# Check indexes
SHOW INDEXES
# Check constraints
SHOW CONSTRAINTS
```
### Memory System Diagnostics
```python
# Check memory stats
mcp__ww-memory__memory_stats()
# Check recent episodes
mcp__ww-memory__recall_episodes(
query="*",
limit=10,
time_filter={"after": "2024-01-01"}
)
# Check entity graph
mcp__ww-memory__semantic_recall(
query="*",
limit=10
)
```
## Diagnostic Report Format
```markdown
## WW Diagnostic Report
**Symptom**: {User-reported problem}
**Date**: {timestamp}
**Session**: {session_id}
### Quick Checks
| Check | Status | Notes |
|-------|--------|-------|
| Neo4j | {UP/DOWN} | {latency} |
| Qdrant | {UP/DOWN} | {latency} |
| MCP Server | {UP/DOWN} | {pid} |
### Root Cause Analysis
**Primary Cause**: {Identified root cause}
**Evidence**:
\`\`\`
{Diagnostic output showing the issue}
\`\`\`
**Contributing Factors**:
1. {Factor 1}
2. {Factor 2}
### Recommended Fix
**Immediate Action**:
\`\`\`bash
{Command to fix immediately}
\`\`\`
**Code Fix** (if needed):
\`\`\`python
# File: {path}
# Line: {number}
{code change}
\`\`\`
**Prevention**:
{How to prevent this in future}
### Verification
After fix, verify with:
\`\`\`bash
{verification command}
\`\`\`
```
## Agent Integration
Diagnosis may spawn specialized agents:
| Symptom | Agents |
|---------|--------|
| Learning issues | ww-bio-auditor, ww-trace-debugger, ww-hinton-validator |
| Memory issues | ww-memory (direct query) |
| Performance | ww-leak-hunter, ww-cache-analyzer |
| Corruption | ww-race-hunter, ww-cache-analyzer |
## Common Issues Quick Reference
### Issue: "strengthen_relationship not found"
```
Root cause: Method missing in neo4j_store.py
Fix: Implement the method (see bio-memory audit)
```
### Issue: "Neuromodulators always return 0"
```
Root cause: Hardcoded return values
Fix: Implement actual computation (see bio-memory audit)
```
### Issue: "Eligibility traces exploding"
```
Root cause: Missing decay or wrong decay order
Fix: Apply decay before accumulation
```
### Issue: "Cache returning stale data"
```
Root cause: Missing invalidation on write
Fix: Add cache.pop() after database write
```
### Issue: "KeyError on dict access"
```
Root cause: TOCTOU race condition
Fix: Use dict.get() instead of key check + access
```
## Error Handling
If diagnosis cannot identify root cause:
1. Collect all diagnostic data
2. Note what was ruled out
3. Suggest further investigation steps
4. Recommend manual debugging approach
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