feat(api): GET /api/workspaces/:id/stats endpoint

skills/memory-discipline/SKILL.md

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+---
+name: memory-discipline
+description: 'Enforce proper session memory recording. Use at: (1) session idle timeout, (2) task completion, (3) explicit /save command, (4) end of significant conversation milestones. Extracts decisions, key info, and action items from the session and writes them to memory storage (files or database).'
+metadata:
+  {
+    "openclaw": { "emoji": "💾", "requires": {} },
+  }
+---
+
+# Memory Discipline Skill
+
+This skill ensures that session knowledge is properly captured and stored, not lost. It is **mandatory** to run this before:
+- Session idle timeout (no user input for X minutes)
+- Task completion
+- Explicit `/save` or `/memory` command
+- Any significant milestone in the conversation
+
+## Why This Exists
+
+Too often agents don't record important information from sessions. This causes:
+- Repeated questions about things the human already told you
+- Lost context between sessions
+- Frustration when "I told you that last time" happens
+
+**This skill makes memory recording REQUIRED, not optional.**
+
+## Workflow
+
+### Step 1: Extract Key Information
+
+Before writing, analyze the session and extract:
+
+| Category | What to capture |
+|----------|-----------------|
+| **Decisions** | Any decision made by the human or jointly (e.g., "we'll use Postgres + pgvector") |
+| **Important Info** | Facts the human provided that should be remembered (e.g., preferences, constraints) |
+| **Action Items** | Things to do later, follow-ups, tasks not yet completed |
+| **Context Changes** | Project state changes, new businesses, new channels |
+| **Lessons** | What worked, what didn't, what to avoid |
+
+### Step 2: Write to Storage
+
+**File-based (current):**
+- Update `memory/YYYY-MM-DD.md` with new entries
+- Update `MEMORY.md` for long-term memory
+- Update `USER.md` if human preferences changed
+- Update project-specific files if applicable
+
+**Database (future - when Postgres/pgvector available):**
+- Write to `session_summaries` table
+- Generate embeddings for RAG context
+- Log to `event_log` table
+
+### Step 3: Confirm in Chat
+
+After saving, say EXACTLY:
+```
+💾 Saved to memory:
+- X decisions
+- X key info items
+- X action items
+
+[If action items exist:]
+TODO: [list each action item]
+```
+
+This confirms to the human that their information was saved.
+
+## Triggers
+
+**Automatic triggers (run yourself):**
+1. Session idle for 5+ minutes (check on heartbeat or cron)
+2. Task marked as complete
+3. Human explicitly asks to save
+
+**Manual triggers (human invokes):**
+- `/save` - Save current session state
+- `/memory` - Show what has been saved this session
+- `/remember <info>` - Manually add something to memory
+
+## Quality Standards
+
+✅ **DO:**
+- Write specific, actionable entries
+- Include context (why this matters)
+- Use bullet points for readability
+- Include dates when relevant
+- Add to appropriate memory file (daily vs long-term)
+
+❌ **DON'T:**
+- Write vague entries like "discussed project"
+- Skip this step "if nothing important happened"
+- Save trivial things (greetings, small talk)
+- Write excessively long entries
+
+## Integration Points
+
+When running this skill, also check:
+1. **TODOs** - Any pending tasks that should be logged?
+2. **Open Threads** - Any ongoing conversations that need continuation notes?
+3. **Project State** - Did any project context change?
+
+## Example Output
+
+```
+💾 Saved to memory:
+- Decision: Use Valkey (not RabbitMQ) for message bus
+- Decision: bge-m3 for embeddings, cogito:14b for local chat
+- Key info: Postgres image already has pgvector built-in
+- Action: Check deployed stack via Portainer at 10.1.1.45
+
+TODO:
+- [ ] Pull bge-m3 model to Ollama
+- [ ] Verify pgvector in postgres image
+- [ ] Draft instance configs for Main + 3 departments
+```