wm

wm — Working Memory for AI Coding Assistants

wm automatically captures tacit knowledge from your coding sessions and surfaces relevant context for each new task. It's the memory layer that helps AI assistants learn how you work.

Supported platforms:

• Claude Code - Full support via plugin
• OpenAI Codex CLI - Alpha support via skill (agent-invoked)

The Problem

LLMs have amnesia. Every conversation starts fresh. The patterns you've established, the constraints you've discovered, the preferences you've revealed—all forgotten.

You end up repeating yourself:

• "Remember, we always use X pattern here"
• "Don't forget the constraint about Y"
• "I prefer Z approach for this kind of problem"

The Solution

wm runs silently in the background:

1. Extract: After each conversation turn, captures tacit knowledge—the wisdom that emerges from how you work, not just what you say
2. Compile: Before each new prompt, filters accumulated knowledge for relevance and injects it as context

The result: AI assistants that remember your patterns across sessions.

What Gets Captured

Tacit knowledge is the unspoken wisdom in how someone works:

• Rationale behind decisions (WHY this approach, not just WHAT was done)
• Paths rejected and why (the judgment in pruning options)
• Constraints discovered through friction
• Preferences revealed by corrections
• Patterns followed without stating

Not captured:

• What happened ("Fixed X", "Updated Y")
• Explicit requests or questions
• Tool outputs or code snippets
• Content from CLAUDE.md (already explicit)

Quickstart: Claude Code

Prerequisites

• Claude Code CLI
• superego (optional, but recommended for extraction triggers)

Option 1: Homebrew (macOS)

brew tap cloud-atlas-ai/wm
brew install wm

Option 2: Cargo (all platforms)

cargo install wm

Option 3: From Source

git clone https://github.com/cloud-atlas-ai/wm.git
cd wm
cargo install --path .

Install the Claude Code Plugin

claude plugin install wm

Initialize in Your Project

cd /your/project
wm init

This creates a .wm/ directory to store accumulated knowledge.

Quickstart: OpenAI Codex CLI (Alpha)

Codex support uses agent skills that can be invoked at decision points. Most features work, but session auto-discovery is limited due to Codex's different session storage format.

What works:

• ✅ Manual knowledge capture/review (state.md, working_set.md)
• ✅ Dive prep with context gathering
• ✅ Compress and pause operations
• ⚠️ Distill requires manual transcript paths (no auto-discovery yet)

# 1. Install the binary (choose one)
brew install cloud-atlas-ai/wm/wm           # macOS
cargo install wm                            # All platforms

# 2. Install the skills
mkdir -p ~/.codex/skills
ln -s /path/to/wm/plugin ~/.codex/skills/wm

# Or download agents individually:
mkdir -p ~/.codex/skills/wm/agents
BASE_URL="https://raw.githubusercontent.com/cloud-atlas-ai/wm/main/plugin/agents"
curl -L -o ~/.codex/skills/wm/agents/dive-prep.md $BASE_URL/dive-prep.md
curl -L -o ~/.codex/skills/wm/agents/review.md $BASE_URL/review.md
curl -L -o ~/.codex/skills/wm/agents/distill.md $BASE_URL/distill.md
curl -L -o ~/.codex/skills/wm/agents/compress.md $BASE_URL/compress.md
curl -L -o ~/.codex/skills/wm/agents/pause.md $BASE_URL/pause.md

Available Agent Skills:

Skill	Support	When to Use
$wm:dive-prep	✅ Full	Prepare focused work session with intent, context, and workflow
$wm:review	✅ Full	Review accumulated knowledge and current context
$wm:compress	✅ Full	Synthesize state.md to higher-level abstractions
$wm:pause	✅ Full	Pause/resume operations (extract, compile, or both)
$wm:distill	⚠️ Manual	Batch extract (requires manual transcript paths)

Typical Workflows:

# Session start - prepare dive context
$wm:dive-prep --intent fix

# Mid-session - review what wm knows
$wm:review

# Maintenance - compress accumulated knowledge
$wm:compress

# Sensitive work - pause extraction
$wm:pause extract

# Manual extraction from Codex session (since auto-discovery isn't supported yet)
# Find your sessions:
ls ~/.codex/sessions/2026/01/*/rollout-*.jsonl
# Extract from specific transcript:
wm extract --transcript ~/.codex/sessions/2026/01/06/rollout-<timestamp>-<uuid>.jsonl

Why limited session discovery?

Codex stores sessions in ~/.codex/sessions/YYYY/MM/DD/ with different naming and structure than Claude Code's ~/.claude/projects/<project-id>/. Auto-discovery support for Codex sessions is tracked in #11.

Manual Commands:

All CLI commands work normally: wm init, wm show state, wm show working, etc.