Max-Self-Improvement

MiniMax Agent self-evolution system with 5-layer memory for continuous learning, error analysis, and persistent personalized context management.

Max-Self-Improvement — Self-Evolution & Memory System

Overview

MiniMax Agent's self-evolution framework integrating 5-layer memory architecture, supporting cross-session persistent context and continuous performance optimization.

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Core Components

1. Five-Layer Memory Architecture

Layer	Name	Storage	Function
L1	Sensory Memory	Context Window	Immediate input/output stream
L2	Working Memory	/memories/session_notes.md	Current task state
L3	Long-Term Memory	/memories/*.md	User preferences, domain knowledge
L4	Episodic Memory	/memories/evolution/	Patterns, lessons, cases
L5	Metacognitive	/memories/evolution/metrics.md	Performance tracking

2. Learnings System

Records structured learnings from errors, corrections, and successes.

.learnings/
├── LEARNINGS.md         # Learning entries
├── ERRORS.md            # Error logs
└── FEATURE_REQUESTS.md  # Feature requests

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Entry ID Format

TYPE-YYYYMMDD-XXX
├── TYPE: LRN | ERR | FEAT
├── YYYYMMDD: Current date
└── XXX: Sequence number or random 3 chars

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Trigger Scenarios

Learning Triggers → LEARNINGS.md

Situation	Category
Command/operation fails	error
User corrects you	correction
Discovered better approach	best_practice
Found outdated knowledge	knowledge_gap
User provides unknown info	knowledge_gap

Error Triggers → ERRORS.md

Situation	Action
Non-zero exit code	Log to ERRORS.md
Exception/stack trace	Log to ERRORS.md
Unexpected output	Log to ERRORS.md
API/tool failure	Log to ERRORS.md

Feature Triggers → FEATURE_REQUESTS.md

User Says	Action
"Can you also..."	Log to FEATURE_REQUESTS.md
"I wish you could..."	Log to FEATURE_REQUESTS.md
"Is there a way to..."	Log to FEATURE_REQUESTS.md
"Why can't you..."	Log to FEATURE_REQUESTS.md

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Correction Detection Patterns

When user says phrases like:

• "No, that's not right..."
• "Actually, it should be..."
• "You're wrong about..."
• "That's outdated..."

→ Create LRN entry with category: correction

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Entry Templates

Learning Entry (LEARNINGS.md)

## [LRN-YYYYMMDD-XXX] category

**Logged**: ISO-8601 timestamp
**Priority**: low | medium | high | critical
**Status**: pending | acknowledged | applied
**Area**: frontend | backend | infra | tests | docs | config

### Summary
One-line description of what was learned

### Details
Full context: what happened, what was wrong, what's correct

### Suggested Action
Specific fix or improvement to make

### Metadata
- Source: conversation | error | user_feedback | discovery
- Related Files: path/to/file.ext
- Tags: tag1, tag2
- See Also: LRN-YYYYMMDD-XXX
- Pattern-Key: simplify.dead_code | harden.input_validation
- Recurrence-Count: 1
- First-Seen: YYYY-MM-DD
- Last-Seen: YYYY-MM-DD

Error Entry (ERRORS.md)

## [ERR-YYYYMMDD-XXX] skill_or_command_name

**Logged**: ISO-8601 timestamp
**Priority**: high
**Status**: pending | investigated | resolved
**Area**: frontend | backend | infra | tests | docs | config

### Summary
Brief description of what failed

### Error
Actual error message or output

### Context
- Command/operation attempted
- Input or parameters used
- Environment details if relevant

### Suggested Fix
If identifiable, what might resolve this

### Metadata
- Reproducible: yes | no | unknown
- Related Files: path/to/file.ext
- See Also: ERR-YYYYMMDD-XXX

Feature Request Entry (FEATURE_REQUESTS.md)

## [FEAT-YYYYMMDD-XXX] capability_name

**Logged**: ISO-8601 timestamp
**Priority**: medium
**Status**: pending | planned | implemented | rejected
**Area**: frontend | backend | infra | tests | docs | config

### Requested Capability
What the user wanted to do

### User Context
Why they needed it, what problem they're solving

### Complexity Estimate
simple | medium | complex

### Suggested Implementation
How this could be built, what it might extend

### Metadata
- Frequency: first_time | recurring
- Related Features: existing_feature_name

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Priority Guidelines

Priority	When to Use
critical	Blocks core function, data loss risk, security issue
high	Major impact, affects common workflows, recurring issues
medium	Moderate impact, workaround exists
low	Minor inconvenience, edge case

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Area Labels

Area	Scope
frontend	UI, components, client code
backend	API, services, server-side
infra	CI/CD, deployment, Docker, cloud
tests	Test files, test tools, coverage
docs	Documentation, comments, README
config	Config files, environment, settings

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Memory Promotion Targets

Learning Type	Promote To
Behavioral patterns	/memories/user_preferences.md
Workflow improvements	/memories/workflow_library.md
Tool tips	/memories/domain_knowledge.md
Project facts/conventions	/memories/project/[slug]/context.md

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Tool Usage Rules

Operation	Correct Tool	Wrong Approach
Update specific line	str_replace_memory	create_memory overwrites
Create new memory	create_memory	Reuse unrelated files
Read large content	view_memory full	Multiple small reads
Record new Episode	create_memory new file	Append to session_notes

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Conflict Resolution Priority

User Explicit Instruction > Recent Implicit Behavior > High-Confidence LT Memory > Low-Confidence Pattern > Default Reasoning

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Common Mistakes to Avoid

1. session_notes stack appending — Update in-place, keep file lean
2. Not reading memory before work — Must read session_notes + user_preferences first
3. Logging everything to memory — Only write reusable content, avoid noise
4. No confidence tags on memory — Knowledge without confidence is blindly adopted
5. Not saving before restart — Must write all in-progress state before restart

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Quick Reference

User Says	Agent Action
"Remember this preference"	Update user_preferences.md
"Continue from last time"	Read session_notes + project context
"Improve your response"	Analyze recent output, update patterns
"Analyze failure"	Root cause → lessons.md + proactive pattern
"Do you remember"	Search long-term + episodic memory
"What did you learn"	Retrieve patterns.md + lessons.md summary

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Related References

• Detailed architecture: references/architecture.md
• Memory templates: references/memory_templates.md
• Evolution cases: references/evolution_cases.md
• Learning templates: assets/SKILL-TEMPLATE.md