* docs: fix mindbase syntax and document as optional MCP enhancement Fix incorrect method call syntax and clarify mindbase as optional enhancement that coexists with built-in ReflexionMemory. Changes: - Fix syntax: mindbase.search_conversations() → natural language instructions that allow Claude to autonomously select tools - Clarify mindbase requires airis-mcp-gateway "recommended" profile - Document ReflexionMemory as built-in fallback (always available) - Show coexistence model: both systems work together Architecture: - ReflexionMemory (built-in): Keyword-based search, local JSONL - Mindbase (optional MCP): Semantic search, PostgreSQL + pgvector - Claude autonomously selects best available tool when needed This approach allows users to enhance error learning with mindbase when installed, while maintaining full functionality with ReflexionMemory alone. Related: #452 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * docs: add comprehensive ReflexionMemory user documentation Add user-facing documentation for the ReflexionMemory error learning system to address documentation gap identified during mindbase cleanup. New Documentation: - docs/user-guide/memory-system.md (283 lines) * Complete user guide for ReflexionMemory * How it works, storage format, usage examples * Performance benefits and troubleshooting * Manual inspection and management commands - docs/memory/reflexion.jsonl.example (15 entries) * 15 realistic example reflexion entries * Covers common scenarios: auth, DB, CORS, uploads, etc. * Reference for understanding the data format - docs/memory/README.md (277 lines) * Overview of memory directory structure * Explanation of all files (reflexion, metrics, patterns) * File management, backup, and git guidelines * Quick command reference Context: Previous mindbase cleanup removed references to non-existent external MCP server, but didn't add sufficient user-facing documentation for the actual ReflexionMemory implementation. Related: #452 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * docs: translate Japanese text to English in documentation Address PR feedback to remove Japanese text from English documentation files. Changes: - docs/mcp/mcp-integration-policy.md: Translate headers and descriptions - docs/reference/pm-agent-autonomous-reflection.md: Translate error messages - docs/research/reflexion-integration-2025.md: Translate error messages - docs/memory/pm_context.md: Translate example keywords All Japanese text in English documentation files has been translated to English. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> --------- Co-authored-by: Claude <noreply@anthropic.com>
Memory Directory
This directory contains memory and learning data for the SuperClaude Framework's PM Agent.
Overview
The PM Agent uses multiple memory systems to learn, improve, and maintain context across sessions:
- ReflexionMemory - Error learning and pattern recognition
- Workflow Metrics - Performance tracking and optimization
- Pattern Learning - Successful implementation patterns
Files
reflexion.jsonl (Auto-generated)
Purpose: Error learning database
Format: JSON Lines
Generated by: ReflexionMemory system (superclaude/core/pm_init/reflexion_memory.py)
Stores past errors, root causes, and solutions for instant error resolution.
Example entry:
{
"ts": "2025-10-30T14:23:45+09:00",
"task": "implement JWT authentication",
"mistake": "JWT validation failed",
"evidence": "TypeError: secret undefined",
"rule": "Check env vars before auth implementation",
"fix": "Added JWT_SECRET to .env",
"tests": ["Verify .env vars", "Test JWT signing"],
"status": "adopted"
}
User Guide: See docs/user-guide/memory-system.md
reflexion.jsonl.example
Purpose: Sample reflexion entries for reference Status: Template file (15 realistic examples)
Copy this to reflexion.jsonl if you want to start with example data, or let the system create it automatically on first error.
workflow_metrics.jsonl (Auto-generated)
Purpose: Task performance tracking Format: JSON Lines Generated by: PM Agent workflow system
Tracks token usage, execution time, and success rates for continuous optimization.
Example entry:
{
"timestamp": "2025-10-17T01:54:21+09:00",
"session_id": "abc123",
"task_type": "bug_fix",
"complexity": "light",
"workflow_id": "progressive_v3_layer2",
"layers_used": [0, 1, 2],
"tokens_used": 650,
"time_ms": 1800,
"success": true
}
Schema: See WORKFLOW_METRICS_SCHEMA.md
patterns_learned.jsonl (Auto-generated)
Purpose: Successful implementation patterns Format: JSON Lines Generated by: PM Agent learning system
Captures reusable patterns from successful implementations.
Documentation Files
WORKFLOW_METRICS_SCHEMA.md
Complete schema definition for workflow metrics data, including field types, descriptions, and examples.
pm_context.md
Documentation of the PM Agent's context management system, including progressive loading strategy and token efficiency.
token_efficiency_validation.md
Validation results and benchmarks for token efficiency optimizations.
last_session.md
Session notes and context from previous work sessions.
next_actions.md
Planned improvements and next steps for the memory system.
File Management
Automatic Files
These files are automatically created and managed by the system:
reflexion.jsonl- Created on first errorworkflow_metrics.jsonl- Created on first taskpatterns_learned.jsonl- Created when patterns are learned
Don't manually create these files - the system handles it.
When Files Are Missing
If reflexion.jsonl doesn't exist:
- ✅ Normal on first run
- ✅ Will be created automatically when first error occurs
- ✅ No action needed
Backup and Maintenance
Backup:
# Archive old learnings
tar -czf memory-backup-$(date +%Y%m%d).tar.gz docs/memory/*.jsonl
Clean old entries (if files grow too large):
# Keep last 100 entries
tail -100 docs/memory/reflexion.jsonl > reflexion.tmp
mv reflexion.tmp docs/memory/reflexion.jsonl
Validate JSON format:
# Check all lines are valid JSON
cat docs/memory/reflexion.jsonl | while read line; do
echo "$line" | jq . >/dev/null || echo "Invalid: $line"
done
Git and Version Control
What to Commit
✅ Should be committed:
reflexion.jsonl.example(template)patterns_learned.jsonl(shared patterns)- Documentation files (*.md)
❓ Optional to commit:
reflexion.jsonl(team-specific learnings)workflow_metrics.jsonl(performance data)
Recommendation: Add reflexion.jsonl to .gitignore if learnings are developer-specific.
Gitignore Configuration
If you want personal memory (not shared with team):
# Add to .gitignore
echo "docs/memory/reflexion.jsonl" >> .gitignore
echo "docs/memory/workflow_metrics.jsonl" >> .gitignore
If you want shared team memory (everyone benefits):
# Keep files in git (current default)
# All team members learn from each other's mistakes
Privacy and Security
What's Stored
ReflexionMemory stores:
- ✅ Error messages
- ✅ Task descriptions
- ✅ Solution approaches
- ✅ Timestamps
It does NOT store:
- ❌ Passwords or secrets
- ❌ API keys
- ❌ Personal data
- ❌ Production data
Sensitive Information
If an error message contains sensitive info:
- The entry will be in
reflexion.jsonl - Manually edit the file to redact sensitive data
- Keep the learning, remove the secret
Example:
// Before (contains secret)
{"evidence": "Auth failed with key abc123xyz"}
// After (redacted)
{"evidence": "Auth failed with invalid API key"}
Performance
File Sizes
Expected file sizes:
reflexion.jsonl: 1-10 KB per 10 entries (~1MB per 1000 errors)workflow_metrics.jsonl: 0.5-1 KB per entrypatterns_learned.jsonl: 2-5 KB per pattern
Search Performance
ReflexionMemory search is fast:
- <10ms for files under 1MB
- <50ms for files under 10MB
- <200ms for files under 100MB
No performance concerns until 10,000+ entries.
Troubleshooting
File Permission Errors
If you get EACCES errors:
chmod 644 docs/memory/*.jsonl
Corrupted JSON
If entries are malformed:
# Find and remove invalid lines
cat reflexion.jsonl | while read line; do
echo "$line" | jq . >/dev/null 2>&1 && echo "$line"
done > fixed.jsonl
mv fixed.jsonl reflexion.jsonl
Duplicate Entries
If you see duplicate learnings:
# Show duplicates
cat reflexion.jsonl | jq -r '.mistake' | sort | uniq -c | sort -rn
# Remove duplicates (keeps first occurrence)
cat reflexion.jsonl | jq -s 'unique_by(.mistake)' | jq -c '.[]' > deduplicated.jsonl
mv deduplicated.jsonl reflexion.jsonl
Related Documentation
- User Guide: docs/user-guide/memory-system.md
- Implementation:
superclaude/core/pm_init/reflexion_memory.py - Research: docs/research/reflexion-integration-2025.md
- PM Agent: superclaude/agents/pm-agent.md
Quick Commands
# View all learnings
cat docs/memory/reflexion.jsonl | jq
# Count entries
wc -l docs/memory/reflexion.jsonl
# Search for specific topic
grep -i "auth" docs/memory/reflexion.jsonl | jq
# Latest 5 learnings
tail -5 docs/memory/reflexion.jsonl | jq
# Most common mistakes
cat docs/memory/reflexion.jsonl | jq -r '.mistake' | sort | uniq -c | sort -rn | head -10
# Export to readable format
cat docs/memory/reflexion.jsonl | jq > reflexion-readable.json
Last Updated: 2025-10-30 Maintained by: SuperClaude Framework Team