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

Phase 1: Search Memories (REQUIRED FIRST STEP)

CRITICAL - ALWAYS SEARCH FIRST: Before file operations, decisions, or implementations, search memories to find existing context:

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

Search-First Benefits (from MCP code execution article):

• ✅ Context efficiency: Only load what you need (not all reference files)
• ✅ Token savings: Search results use fewer tokens than loading all patterns
• ✅ Progressive disclosure: Discover tools/patterns on-demand, not upfront

When to load references:

• ✅ If search found relevant memories → Skip references, use memories instead
• ✅ If search found nothing → Load appropriate reference file from references/

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" }
})

Privacy & Security: What NOT to Store

NEVER store sensitive data in memories:

❌ Secrets:

• API keys, access tokens, passwords
• Environment variables with API_KEY, SECRET, PASSWORD, TOKEN
• Private keys, certificates, credentials

❌ Personal Identifiable Information (PII):

• Email addresses (personal or customer)
• Phone numbers
• Social Security Numbers, Tax IDs
• Credit card numbers, payment info

❌ Sensitive Configuration:

• Production database connection strings with passwords
• OAuth client secrets
• Webhook secrets, signing keys

✅ Safe to store:

• General architecture patterns ("We use JWT for auth")
• Tool choices ("We prefer PostgreSQL")
• Workflow rules ("Always run tests before commit")
• Non-sensitive configuration ("API base URL: https://api.example.com")

Why this matters: Memories are stored locally but could be exported or synced. Following privacy-by-default prevents accidental leaks.

See references/privacy.md for detailed examples and automatic filtering patterns.

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 (ONLY if search didn't help):

• Search first, then load references only if needed
• references/devops/ - Topic-specific DevOps patterns (git, testing, architecture, etc.)
• references/capture-examples.md - Manual storage templates
• references/troubleshooting.md - Common issues
• references/privacy.md - What NOT to store (secrets, PII)

---

Remember:

1. ALWAYS search first - Most efficient use of context
2. Skip references if search succeeded - Memories are more relevant than examples
3. Trust automatic capture - Handles most patterns
4. The learning loop works best when you search before every task