terminalskills/skills

claude-mem

>- Add persistent memory to Claude Code that survives across sessions. Use when: maintaining continuity across Claude Code sessions, building agents with persistent project memory, avoiding repeated context setup. Covers claude-mem (AI-compressed session logs) and Claude Subconscious (Letta-based background agent).

First seen Apr 16, 2026

Installation

$ npx skills add terminalskills/skills --skill claude-mem

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Repository health

Stars 146
License LICENSE
Default branch main
Open issues 1
Status Active

Skill metadata

Parsed from SKILL.md frontmatter.

Version2.0.0
LicenseApache-2.0
CompatibilityClaude Code, Node.js 18+
Declared agents claude-code
More metadata
author
terminal-skills
version
2.0.0
category
productivity
tags
["claude-code","memory","persistence","context","session"]

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 5,118 B
  • docs SUMMARY.md 331 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 23 installs

SKILL.md

Claude Code Persistent Memory

Overview

Claude Code forgets everything between sessions. Two open-source tools solve this by automatically capturing context and injecting it into future sessions:

  • claude-mem — captures session activity, compresses it with AI, injects relevant memories on next session. Lightweight, local-first.
  • Claude Subconscious — a background Letta agent that watches sessions, builds up memory over time, and whispers guidance back. Cloud or self-hosted.

Both eliminate the need to re-explain context when returning to a project.

Instructions

Option A: claude-mem (Local AI Compression)

GitHub: thedotmack/claude-mem

Setup

npm install -g claude-mem
cd your-project
claude-mem init
claude-mem setup-hooks

This creates .claude-mem/ with config, compressed memories, and an index. Hooks auto-capture after each session and auto-inject before the next.

How It Works

  1. Capture — hooks into Claude Code session, records interactions
  2. Compress — AI summarizes session into structured memory (decisions, code changes, learnings)
  3. Store — compressed memories saved to .claude-mem/ directory
  4. Retrieve — on new session, relevant memories injected into context

Commands

claude-mem capture                     # Capture current session
claude-mem inject                      # Inject memories into context
claude-mem search "auth flow"          # Semantic search through memories
claude-mem list                        # List all memories
claude-mem stats                       # Show memory stats
claude-mem compress                    # Reduce storage for old memories

Configuration

{
  "compression": {
    "model": "claude-sonnet-4-20250514",
    "strategy": "smart"
  },
  "inject": {
    "maxMemories": 10,
    "relevanceThreshold": 0.7,
    "strategy": "semantic"
  }
}

Strategies: smart (AI picks what's important), full (captures everything), minimal (only decisions and errors).

Option B: Claude Subconscious (Letta Background Agent)

GitHub: letta-ai/claude-subconscious

Setup

/plugin marketplace add letta-ai/claude-subconscious
/plugin install claude-subconscious@claude-subconscious
export LETTA_API_KEY="your-api-key"

Get your API key from app.letta.com. Or self-host:

pip install letta
letta server --port 8283
export LETTA_BASE_URL="http://localhost:8283"

Modes

Mode Behavior Token Cost
whisper (default) Short guidance before each prompt Low
full Full memory blocks + message history Higher
off Disabled None

Which to Choose

claude-mem Claude Subconscious
Storage Local files (.claude-mem/) Letta cloud or self-hosted
Cost Uses your Claude API for compression Requires Letta API key (free tier)
Latency Near-zero (local) ~1-2s per whisper
Memory style Compressed session summaries Continuous learning agent
Best for Local-first, privacy-sensitive Rich cross-session context

Examples

Example 1: Session Continuity with claude-mem

# Session 1: Work on auth module
$ claude-mem stats
Memories: 12 | Storage: 45KB | Last capture: 2 hours ago

# Session 2: Return to project — auto-injected context
# Claude already knows: "You implemented JWT auth with RS256, refresh tokens in Redis"

Example 2: Architecture Recall with Subconscious

After discussing a REST-to-GraphQL migration, you start a new session:

[subconscious] Last session you decided to switch from REST to GraphQL for the
user service. Migration is 60% done — resolvers for User and Project are complete,
Order and Payment still need conversion. You preferred code-first schema with TypeGraphQL.

Guidelines

  • Pair with CLAUDE.md — use CLAUDE.md for static project context, persistent memory for dynamic decisions
  • One tool per project — don't run both claude-mem and Subconscious simultaneously
  • For claude-mem: set relevanceThreshold higher (0.8+) if too much context is injected
  • For Subconscious: whisper mode gives 90% of the value at lower token cost
  • Add .claude-mem/memories/ to .gitignore for private projects
  • Memory quality depends on session length — short sessions produce less useful memories