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cass-memory

cass-memory

github.com/johnlindquistAgent workflows2643 installsUpdated 45w ago
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About cass-memory

cass-memory is a CLI-based system for coding agents that builds a personal playbook from coding sessions. It surfaces relevant rules and past examples, then lets users review and refine them with feedback and outcomes.

Key features

  1. 01Task-specific context and past examples
  2. 02Pattern extraction from recent sessions
  3. 03Playbook rule management
  4. 04Helpful or harmful rule feedback
  5. 05Session outcome and rule statistics

Use cases

  1. 01Load relevant coding guidance before a task
  2. 02Extract reusable patterns from recent work
  3. 03Review and prune outdated playbook rules

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/johnlindquist/claude --skill cass-memory

After installing, type/cass-memoryin Claude Code to confirm it loaded.

Details

From the project README

CASS Memory - Contextual Learning System

Build and use a personal playbook of coding patterns learned from your sessions.

Prerequisites

The cm CLI should be available (part of cass-memory system).

Initialize:

cm init
# Or with a starter playbook
cm init --starter typescript
cm init --starter react
cm init --starter python
cm init --starter go

CLI Reference

Get Context for a Task
# THE main command - get relevant rules before starting work
cm context "Description of your task" --json

This returns:

  • Relevant rules from your playbook
  • Anti-patterns to avoid
  • History snippets from similar past work
Reflection (Extract Patterns)
# Run reflection on recent sessions
cm reflect --json

# Specify lookback period
cm reflect --days 7 --json
cm reflect --days 30 --json
Playbook Management
# List all rules
cm playbook list --json

# Get specific rule details
cm playbook get b-8f3a2c --json

# Add a new rule
cm playbook add "Always use optional chaining for nested object access" --json
Feedback on Rules
# Mark rule as helpful
cm mark b-8f3a2c --helpful --json
cm mark b-8f3a2c --helpful --reason "Prevented null error" --json

# Mark rule as harmful
cm mark b-8f3a2c --harmful --json
cm mark b-8f3a2c --harmful --reason "Caused false positive" --json
Record Session Outcomes
# Record success
cm outcome --status success --json
cm outcome --status success --rules "b-8f3a2c,b-4d2e1f" --json

# Record failure
cm outcome --status failure --text "Build failed due to type error" --json

# Mixed results
cm outcome --status mixed --text "Partial completion" --json
Statistics
# Get playbook stats
cm stats --json
Top Rules
# Show most effective rules
cm top --json
cm top 5 --json
cm top 20 --json
Health Check
# Check system health
cm doctor --json

# Auto-fix issues
cm doctor --fix --json
Find Stale Rules
# Rules without recent feedback
cm stale --json
cm stale --days 30 --json
cm stale --days 60 --json
Validate Rules
# Validate a proposed rule against history
cm validate "Proposed rule text" --json
Explain Rule Origin
# Show evidence and reasoning for a rule
cm why b-8f3a2c --json
Usage Statistics
cm usage --json
Starter Playbooks
# List available starters
cm starters --json

Workflow Patterns

Session Start
# Get context before starting a task
cm context "Implement user authentication with JWT" --json
During Work

When a rule helps:

cm mark b-8f3a2c --helpful --json

When a rule leads astray:

cm mark b-8f3a2c --harmful --reason "Not applicable to this framework" --json
Session End
# Record outcome
cm outcome --status success --rules "b-8f3a2c,b-4d2e1f" --json
Periodic Maintenance
# Weekly: Run reflection to extract new patterns
cm reflect --days 7 --json

# Monthly: Review stale rules
cm stale --days 30 --json

# Check system health
cm doctor --json
Building Your Playbook
# Manually add a pattern you've learned
cm playbook add "Use React.memo() for components receiving complex objects as props" --json

# After adding, use it in context queries
cm context "Create a list component with filtering" --json

Rule Lifecycle

  1. Creation - Rules emerge from reflection or manual addition
  2. Usage - Rules surface in context queries
  3. Feedback - Mark as helpful/harmful based on experience
  4. Evolution - High-feedback rules rise, low-feedback rules become stale
  5. Retirement - Stale rules get reviewed and pruned

Best Practices

  1. Always get context first - Run cm context "task" before starting work
  2. Provide feedback - Mark rules as helpful/harmful
  3. Record outcomes - Track session success/failure
  4. Run reflection regularly - Weekly reflection extracts new patterns
  5. Review stale rules - Don't let old rules accumulate
  6. Add rules manually - When you learn something important

Integration Tips

Pre-Task Context

Before any significant coding task:

CONTEXT=$(cm context "Your task description" --json)
# Use context to inform your approach
Post-Session Recording

At end of coding session:

cm outcome --status success --text "Completed feature X" --json

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