Guide for storing enriched memories that capture decisions, preferences, and context. Use when making significant decisions or learning user preferences.
/plugin marketplace add designnotdrum/brain-jar/plugin install shared-memory@brain-jarThis skill is limited to using the following tools:
IMPORTANT: Before using memory tools, ensure the MCP server is built and configured:
# Check if built
ls ~/.claude/plugins/cache/brain-jar/shared-memory/*/dist/index.js 2>/dev/null || echo "NOT_BUILT"
If NOT_BUILT, run the setup:
node ~/.claude/plugins/cache/brain-jar/shared-memory/*/run.js &
sleep 15
Then check for Mem0 config:
cat ~/.config/brain-jar/config.json 2>/dev/null || echo "NOT_CONFIGURED"
If NOT_CONFIGURED, ask user for their Mem0 API key (get one at https://app.mem0.ai), then create config:
mkdir -p ~/.config/brain-jar
cat > ~/.config/brain-jar/config.json << 'EOF'
{
"mem0_api_key": "USER_API_KEY_HERE",
"default_scope": "global",
"auto_summarize": true
}
EOF
Note: Local storage works without Mem0 config - cloud sync is optional.
After setup, user must restart Claude Code for MCP to register.
Store memories when you observe:
Bad (too dry):
User chose Neon for database.
Good (captures context and sentiment):
User chose Neon over Supabase for Postgres hosting - appreciated the more generous
free tier limits. Showed strong preference for managed solutions: "I'm not running
my own infra" - values simplicity and time savings over control.
Include:
global - Personal preferences, general learnings, cross-project patternsproject:<name> - Specific to current project (detect from working directory)Use global for preferences that apply everywhere. Use project: for architectural
decisions, tech choices, and patterns specific to one codebase.
Before:
Use natural recall language:
preference - Likes/dislikesdecision - Specific choices madearchitecture - System design patternspersonality - Working style, communication preferencesproject - Project-specific contextsession-summary - End-of-session consolidationprofile-context - Background context for profile preferencesprofile-learning - Observations that inform the user profileFor structured user profile management (name, role, tech preferences, working style),
use the learning-about-you skill instead of storing as freeform memories.
Use memories for:
Use profile for:
The profile is queryable and shared across all brain-jar plugins. Memories provide the context and "why" behind profile entries.
Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, or applications. Generates creative, polished code that avoids generic AI aesthetics.
This skill should be used when the user asks to "create a hookify rule", "write a hook rule", "configure hookify", "add a hookify rule", or needs guidance on hookify rule syntax and patterns.