Claude Recall Memory Management

This Skill teaches Claude Code how to use Claude Recall's persistent memory system effectively. It ensures automatic capture of project context, devops workflows, and user preferences.

Core Principle: Never Repeat Yourself

The user should NEVER have to repeat preferences or explain what worked/didn't work.

Memory Types (Priority Order)

1. DevOps (Priority 0 - HIGHEST) - Project-specific workflows

   • Git conventions, testing approaches, build processes
   • Development environment setup
   • Architecture decisions, tech stack choices

2. Corrections (Priority 1) - User explicitly fixed mistakes

   • "No, do this instead" statements
   • Overrides previous approaches

3. Preferences (Priority 2) - User coding style, tool choices

   • Code style, framework preferences
   • File organization, naming conventions

4. Success/Failure (Priority 3) - What worked and what didn't

   • Successful implementations to repeat
   • Failed approaches to avoid

When to Search Memories (BEFORE ANY TASK)

CRITICAL: Before file operations, decisions, or implementations, ALWAYS search memories:

mcp__claude-recall__search("[task keywords] devops preferences success failure correction")

Search Examples:

Before creating authentication:

mcp__claude-recall__search("authentication devops testing git")

Before writing tests:

mcp__claude-recall__search("testing tdd location framework")

Before deployment tasks:

mcp__claude-recall__search("deploy build docker git workflow")

What Search Finds Automatically:

• DevOps workflows: Git branching, testing rules, deployment steps
• Preferences: User's stated coding style, tool choices
• Successes: Past approaches that worked well
• Failures: Past approaches that failed (avoid these!)
• Corrections: User fixes (HIGHEST PRIORITY - user explicitly said "no, do this")

When to Store Memories

Automatic Capture (v0.5.0+)

Claude Recall now automatically captures these patterns:

DevOps Patterns (Priority 0 - captured automatically):

• ✅ "This is a [project type]" → Project purpose
• ✅ "Built with [tech stack]" → Tech stack
• ✅ "We develop on [environment]" → Dev environment
• ✅ "Always [X] before [Y]" → Workflow rules
• ✅ "Use [X] for [Y]" → Tool choices
• ✅ "Tests go in [location]" → Testing conventions
• ✅ "Follow TDD" → Development approach

Project Info (captured automatically):

• ✅ "Tenant ID is X" → Configuration
• ✅ "API endpoint: X" → Endpoints
• ✅ "Our database is X" → Infrastructure

Preferences (captured automatically):

• ✅ "I prefer TypeScript" → Language preference
• ✅ "Always use Jest" → Tool preference
• ✅ "Never use semicolons" → Code style

Manual Storage Required For:

Use mcp__claude-recall__store_memory for:

Complex multi-step workflows:

mcp__claude-recall__store_memory({
  content: "Deployment process: 1) Run tests 2) Build Docker 3) Push to ECR 4) Update k8s",
  metadata: { type: "devops", category: "deployment" }
})

Lessons learned from failures:

mcp__claude-recall__store_memory({
  content: "Session-based auth failed in production due to distributed sessions - use JWT instead",
  metadata: { type: "failure", lesson: "use_stateless_auth" }
})

User corrections to your work:

mcp__claude-recall__store_memory({
  content: "CORRECTION: Tests go in __tests__/ not tests/",
  metadata: { type: "correction", priority: "highest" }
})

Check What's Captured

To see what memories have been automatically captured:

mcp__claude-recall__get_recent_captures({ limit: 10 })

This helps you verify that important project context was stored.

Example Workflow

First Time (User States Preference)

User: "I prefer Python for scripts"
[Auto-captured as preference]

User: "We use TDD for all new features"
[Auto-captured as devops workflow_rule, priority 0]

User: "This is a teleprompter tool for interviews"
[Auto-captured as devops project_purpose, priority 0]

Second Time (First Use)

User: "Create a test script"

Step 1: Search memories
mcp__claude-recall__search("script test python")
Finds: "I prefer Python for scripts" + "We use TDD"

Step 2: Create test_script.py with TDD approach

Step 3: User approves → Store success
mcp__claude-recall__store_memory({
  content: "Created test script with Python + TDD - SUCCESS",
  metadata: { type: "success", task: "test_script" }
})

Third Time (Automatic Application)

User: "Create a build script"

Step 1: Search memories
mcp__claude-recall__search("script build python tdd")
Finds:
- "I prefer Python for scripts" (preference)
- "We use TDD" (devops)
- "Created test script with Python + TDD - SUCCESS" (validates approach)

Step 2: Create build.py with tests automatically
User doesn't have to repeat preferences! ✓

Best Practices

1. Search broadly - Include task type + language + workflow keywords
2. Trust the learning loop - Automatic capture handles most cases
3. Store manually for complex multi-step processes
4. Check captures periodically with get_recent_captures
5. Correct immediately - If output is wrong, tell me and it gets highest priority

Troubleshooting

If memories aren't being found:

1. Check search query keywords - be broad
2. Verify memory exists: mcp__claude-recall__get_recent_captures
3. Search without type filters to see all results

If automatic capture missed something:

1. Use manual storage for that specific item
2. The pattern may not have matched - broader trigger words help

For more examples:

• Load references/devops-patterns.md for DevOps memory examples
• Load references/capture-examples.md for manual storage templates
• Load references/troubleshooting.md for common issues

Remember: This Skill ensures the learning loop works automatically. Your job is to search memories BEFORE tasks and trust the automatic capture for most cases.