Memory Management & Knowledge Persistence Skill

[IMPORTANT] Use TaskCreate to break ALL work into small tasks BEFORE starting — including tasks for each file read. This prevents context loss from long files. For simple tasks, AI MUST ATTENTION ask user whether to skip.

Quick Summary

Goal: Persist patterns, decisions, and task progress across sessions using two complementary memory systems.

Workflow:

File Checkpoints — Save task-specific context to plans/reports/checkpoint-*.md every 30-60 min
MCP Memory Graph — Store reusable knowledge (patterns, decisions, bug fixes) as typed entities with relations
Recovery — On context loss, find latest checkpoint via Glob, read it, resume from documented next steps

Key Rules:

Use file checkpoints for task-specific progress; MCP memory for cross-session knowledge
Create checkpoints before expected context compaction and at key milestones
Always include Recovery Instructions in checkpoint files

Be skeptical. Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence percentages (Idea should be more than 80%).

Memory Management & Knowledge Persistence

Build and maintain a knowledge graph of patterns, decisions, and learnings across sessions. Also provides external file-based checkpoints for long-running tasks.

Two Memory Systems

| System | Storage | Use Case | Persistence | | -------------------- | ------------------------ | ------------------------------ | --------------- | | MCP Memory Graph | In-memory graph database | Patterns, decisions, learnings | Cross-session | | File Checkpoints | plans/reports/*.md | Task progress, analysis | Permanent files |

Use MCP Memory for reusable knowledge. Use File Checkpoints for task-specific context.

Part 1: File-Based External Memory (Checkpoints)

When to Create File Checkpoints

Starting complex multi-step tasks (investigation, planning, implementation)
Every 30-60 minutes during long tasks
At key milestones
Before expected context compaction
After completing significant analysis phases

Checkpoint File Location

Files saved to: plans/reports/checkpoint-{timestamp}-{slug}.md

CHECKPOINT_CREATE Protocol

Create a checkpoint file with this structure:

# Memory Checkpoint: {Task Description}

> Created: {ISO timestamp}
> Task Type: {investigation|planning|bugfix|feature|docs}
> Phase: {current phase number/name}

## Task Context

{What you're working on and why}

## Key Findings

{Critical discoveries and insights - be specific with file paths and line numbers}

## Files Analyzed

| File              | Purpose     | Status   |
| ----------------- | ----------- | -------- |
| path/file.cs:line | description | ✅/🔄/⏳ |

## Progress

- [x] Completed items
- [ ] In-progress items
- [ ] Remaining items

## Important Context

{Information that must be preserved - decisions, assumptions, rationale}

## Next Steps

1. {Immediate next action}
2. {Following action}

## Recovery Instructions

{Exact steps to resume: which file to read, which line to continue from}

CHECKPOINT_RECOVER Protocol

When recovering from a checkpoint:

Search for latest checkpoint: Glob("plans/reports/checkpoint-*.md")
Read the checkpoint file
Load any referenced analysis files
Review Progress section
Continue from documented Next Steps
Create new checkpoint after resuming

Auto-Checkpoint (PreCompact Hook)

The system automatically creates checkpoints before context compaction. These auto-checkpoints are minimal - for better context preservation, create manual checkpoints using /checkpoint.

Part 2: MCP Memory Graph (Knowledge Persistence)

Memory Entity Types

| Entity Type | Purpose | Examples | | ----------------- | -------------------------------------- | ------------------------------ | | Pattern | Recurring code patterns | CQRS, Validation, Repository | | Decision | Architectural/design decisions | Why we chose X over Y | | BugFix | Bug solutions for future reference | Race condition fixes | | ServiceBoundary | Service ownership and responsibilities | Growth owns Employees | | SessionSummary | End-of-session progress snapshots | Task progress, next steps | | Dependency | Cross-service dependencies | Growth depends on Accounts | | AntiPattern | Patterns to avoid | Don't call side effects in cmd |

Memory Operations

Create New Entity

mcp__memory__create_entities([
    {
        name: 'EmployeeValidationPattern',
        entityType: 'Pattern',
        observations: [
            'Use project validation fluent API (see docs/project-reference/backend-patterns-reference.md)',
            'Chain with .And() and .AndAsync()',
            "Return validation result, don't throw",
            'Location: {Service}.Application/UseCaseCommands/'
        ]
    }
]);

Create Relationships

mcp__memory__create_relations([
    {
        from: 'ServiceA',
        to: 'ServiceB',
        relationType: 'depends_on'
    },
    {
        from: 'EmployeeEntity',
        to: 'UserEntity',
        relationType: 'syncs_from'
    }
]);

Add Observations

mcp__memory__add_observations([
    {
        entityName: 'EmployeeValidationPattern',
        contents: [
            'Also supports .AndNot() for negative validation',
            'Use .Of<ICqrsRequest>() for type conversion (see docs/project-reference/backend-patterns-reference.md)'
        ]
    }
]);

Search Knowledge

// Search by query
mcp__memory__search_nodes({ query: 'validation pattern' });

// Open specific entities
mcp__memory__open_nodes({
    names: ['EmployeeValidationPattern', 'ServiceAModule']
});

// Read entire graph
mcp__memory__read_graph();

Delete Outdated Knowledge

// Delete entities
mcp__memory__delete_entities({ entityNames: ['OutdatedPattern'] });

// Delete specific observations
mcp__memory__delete_observations([
    {
        entityName: 'EmployeeValidationPattern',
        observations: ['Outdated observation text']
    }
]);

// Delete relations
mcp__memory__delete_relations([
    {
        from: 'OldService',
        to: 'NewService',
        relationType: 'depends_on'
    }
]);

When to Save to Memory

Always Save

Discovered Patterns: New code patterns not in documentation
Bug Solutions: Complex bugs with non-obvious solutions
Service Boundaries: Which service owns what
Architectural Decisions: Why a particular approach was chosen
Anti-Patterns: Mistakes to avoid

Save at Session End

// Session summary template
mcp__memory__create_entities([
    {
        name: `Session_${taskName}_${date}`,
        entityType: 'SessionSummary',
        observations: [
            `Task: ${taskDescription}`,
            `Completed: ${completedItems.join(', ')}`,
            `Remaining: ${remainingItems.join(', ')}`,
            `Key Files: ${keyFiles.join(', ')}`,
            `Discoveries: ${discoveries.join(', ')}`,
            `Next Steps: ${nextSteps.join(', ')}`
        ]
    }
]);

Memory Retrieval Patterns

Session Start Protocol

// 1. Search for related context
const results = mcp__memory__search_nodes({
    query: 'current feature or task keywords'
});

// 2. Load relevant entities
mcp__memory__open_nodes({
    names: results.entities.map(e => e.name)
});

// 3. Check for incomplete sessions
mcp__memory__search_nodes({ query: 'SessionSummary Remaining' });

Before Implementation

// Check for existing patterns
mcp__memory__search_nodes({ query: 'CQRS command pattern' });

// Check for anti-patterns
mcp__memory__search_nodes({ query: 'AntiPattern command' });

// Check for related decisions
mcp__memory__search_nodes({ query: 'Decision validation' });

After Bug Fix

// Save the fix
mcp__memory__create_entities([
    {
        name: `BugFix_${bugName}`,
        entityType: 'BugFix',
        observations: [
            `Symptom: ${symptomDescription}`,
            `Root Cause: ${rootCause}`,
            `Solution: ${solution}`,
            `Files: ${affectedFiles.join(', ')}`,
            `Prevention: ${preventionTip}`
        ]
    }
]);

Knowledge Graph Structure

┌─────────────────────────────────────────────────────────────┐
│                     Project Knowledge                       │
├─────────────────────────────────────────────────────────────┤
│  Services                                                   │
│  ├── ServiceA ──depends_on──> AccountsService               │
│  ├── ServiceB ──depends_on──> AccountsService               │
│  └── ServiceC ──depends_on──> AccountsService               │
│                                                             │
│  Patterns                                                   │
│  ├── CQRSCommandPattern                                     │
│  ├── CQRSQueryPattern                                       │
│  ├── EntityEventPattern                                     │
│  └── ValidationPattern                                      │
│                                                             │
│  Entities                                                   │
│  ├── Employee ──syncs_from──> User                          │
│  ├── Company ──syncs_from──> Organization                   │
│  └── LeaveRequest ──owned_by──> ServiceA                     │
│                                                             │
│  Sessions                                                   │
│  ├── Session_LeaveRequest_2025-01-15                        │
│  └── Session_EmployeeImport_2025-01-14                      │
└─────────────────────────────────────────────────────────────┘

Importance Scoring

When saving observations, prioritize:

| Score | Criteria | | ----- | ------------------------------------------- | | 10 | Critical bug fixes, security issues | | 8-9 | Architectural decisions, service boundaries | | 6-7 | Code patterns, best practices | | 4-5 | Session summaries, progress notes | | 1-3 | Temporary notes, exploration results |

Memory Maintenance

Weekly Cleanup

// Find old session summaries (> 30 days)
mcp__memory__search_nodes({ query: 'SessionSummary' });

// Delete outdated sessions
mcp__memory__delete_entities({
    entityNames: ['Session_OldTask_2024-12-01']
});

Consolidation

When multiple observations cover same topic:

// 1. Read existing entity
mcp__memory__open_nodes({ names: ['PatternName'] });

// 2. Delete fragmented observations
mcp__memory__delete_observations([
    {
        entityName: 'PatternName',
        observations: ['Fragment 1', 'Fragment 2']
    }
]);

// 3. Add consolidated observation
mcp__memory__add_observations([
    {
        entityName: 'PatternName',
        contents: ['Consolidated comprehensive observation']
    }
]);

Quick Reference

Create: mcp__memory__create_entities / mcp__memory__create_relations Read: mcp__memory__read_graph / mcp__memory__open_nodes / mcp__memory__search_nodes Update: mcp__memory__add_observations Delete: mcp__memory__delete_entities / mcp__memory__delete_observations / mcp__memory__delete_relations

Part 3: Integration with Workflows

Long-Running Task Memory Pattern

All long-running workflows should follow this pattern:

┌─────────────────────────────────────────────────────────┐
│ TASK START                                               │
│   └── Create initial checkpoint with task context        │
│   └── Initialize todo list                               │
│                                                          │
│ EVERY 20-30 OPERATIONS                                   │
│   └── Update checkpoint with progress                    │
│   └── Update todo list status                            │
│                                                          │
│ MILESTONE REACHED                                         │
│   └── Create detailed checkpoint                         │
│   └── Save key findings to MCP memory (if reusable)      │
│                                                          │
│ BEFORE COMPACTION (auto via PreCompact hook)             │
│   └── Auto-checkpoint created by system                  │
│                                                          │
│ AFTER COMPACTION / SESSION RESUME                        │
│   └── Read latest checkpoint                             │
│   └── Search MCP memory for relevant context             │
│   └── Continue from documented Next Steps                │
│                                                          │
│ TASK COMPLETE                                             │
│   └── Final checkpoint with summary                      │
│   └── Save reusable patterns to MCP memory               │
│   └── Clean up temporary checkpoints                     │
└─────────────────────────────────────────────────────────┘

Checkpoint Naming Convention

| Type | Format | Example | | ----------------- | ------------------------------------------- | -------------------------------------- | | Manual checkpoint | checkpoint-{YYMMDD}-{HHMM}-{slug}.md | checkpoint-250106-1430-user-auth.md | | Auto checkpoint | memory-checkpoint-{timestamp}.md | memory-checkpoint-20250106-143000.md | | Analysis notes | {type}-{date}-{slug}.md | analysis-250106-payment-flow.md | | Task notes | .ai/workspace/analysis/{slug}.analysis.md | Used by feature-implementation |

Related Commands & Skills

| Command/Skill | Purpose | | ------------------------ | ----------------------------------- | | /checkpoint | Create manual memory checkpoint | | /context | Load project context | | /compact | Manually trigger context compaction | | /watzup | Generate progress summary | | feature-implementation | Uses task analysis notes pattern | | debug-investigate | Uses investigation logs | | feature-investigation | Uses analysis report pattern |

Memory Decision Matrix

| Context Type | Storage | Why | | ----------------------- | --------------- | ------------------------ | | Task progress | File checkpoint | Specific to current task | | Code patterns | MCP memory | Reusable across sessions | | Bug solutions | MCP memory | Helps future debugging | | Service boundaries | MCP memory | Architectural knowledge | | Investigation findings | File checkpoint | Task-specific analysis | | Architectural decisions | MCP memory | Long-term knowledge |

learn
context-optimization

Closing Reminders

MANDATORY IMPORTANT MUST ATTENTION break work into small todo tasks using TaskCreate BEFORE starting
MANDATORY IMPORTANT MUST ATTENTION search codebase for 3+ similar patterns before creating new code
MANDATORY IMPORTANT MUST ATTENTION cite file:line evidence for every claim (confidence >80% to act)
MANDATORY IMPORTANT MUST ATTENTION add a final review todo task to verify work quality

Agent Skills: Memory Management & Knowledge Persistence

Install this agent skill to your local

Skill Files