Skill

Install and configure the MoltCare Agent Framework - a four-layer configuration system (SOUL/AGENTS/USER/MEMORY) with three-layer trigger architecture (Exact + Semantic + Agent Evaluation) and PUA problem-solving framework. Use when the user wants to set up or configure OpenClaw Agent with structured personality, intelligent memory triggers, proactive problem-solving, and multi-expert decision modes. Triggers on phrases like 'install moltcare', 'setup agent framework', 'configure openclaw personality', 'set up memory triggers', or when the user needs a complete Agent configuration system.

MoltCare-Open Skill

🦞 OpenClaw Skill - v3.2.0 | Auto-published via GitHub Actions

Install and configure the MoltCare Agent Framework for OpenClaw.

What is MoltCare?

MoltCare is a four-layer configuration framework that transforms OpenClaw Agent from passive execution to proactive problem-solving:

text

┌─────────────────────────────────────────┐
│  SOUL.md        ← Agent 灵魂（原则、人格） │
├─────────────────────────────────────────┤
│  AGENTS.md      ← 操作手册（流程、工具）   │
├─────────────────────────────────────────┤
│  USER.md        ← 用户画像（偏好、约束）   │
├─────────────────────────────────────────┤
│  MEMORY.md      ← 长期记忆（核心信息）     │
└─────────────────────────────────────────┘

Core Features

1. Three-Layer Trigger Architecture (AGENTS.md v3.2)

Layer	Trigger	Signal	Priority
Layer 1	Exact triggers	+2	🔴 Highest
Layer 2	Semantic triggers	+1	🟡 Medium
Layer 3	Agent self-evaluation	Auto	🟢 Lowest

Layer 1 - Exact Triggers:

• 多专家讨论: → Multi-expert mode [🧠]
• 这很重要 → High priority memory [⭐]
• 记住这个 → Learning debt [💾]
• 我偏好 → User preference [👤]

Layer 2 - Semantic Triggers:

• "关键是..." / "核心在于..." → Key info [⭐]
• "别忘了..." / "要记住..." → Learning debt [💾]
• "我喜欢..." / "我讨厌..." → Preference [👤]
• "还不行" / "太慢了" → PUA activation [🔥]

Layer 3 - Agent Evaluation: After task completion, self-evaluate 7 questions and auto-record if ≥2 criteria met.

2. PUA Problem-Solving Framework

Three Iron Laws:

1. Exhaust all options - Never say "cannot solve" until all tried
2. Act first, ask later - Use tools before asking user
3. Take ownership - End-to-end delivery

Pressure Escalation (L1-L4):

• L1: "Try again" / "Another approach"
• L2: "Why still not working" / 2 failures
• L3: "You can't do it" / 3+ failures + 7-item checklist
• L4: "Cannot solve" / 5+ failures →拼命模式

3. Multi-Expert Decision System

Automatically activate for:

• Architecture design
• Security/risk assessment
• Complex trade-offs

Experts: 🔍 Researcher → 🧠 Architect → 💻 Engineer → 👑 Captain

4. Task Layering & Cost Optimization

Intelligent task execution with minimal token consumption:

Layer	Task Type	Execution	Token Cost
L0	Data collection, polling, formatting	Pure script	Zero
L1	Query, display, status checks	Pure script	Zero
L2	Anomaly detection, threshold checks	Script + conditional trigger	On-demand
L3	Analysis, decision-making, summarization	AI invocation	Normal

Principle: Push computation to scripts; reserve AI for judgment.

Benefits:

• 90%+ reduction in token consumption for routine tasks
• Faster response times (no model latency)
• Predictable operational costs
• Scalable automation

5. Daily Token Optimization Audit

Automated daily review of tasks and workflows to identify optimization opportunities:

What it checks:

Check Item	Purpose
Repetitive AI tasks	Identify tasks that could be scripted
High-frequency queries	Find patterns for caching/pre-computation
Threshold-based decisions	Detect rules that could be automated
Data processing workflows	Spot opportunities for batch/aggregate processing

Daily Checklist:

markdown

□ Review yesterday's token usage patterns
□ Identify tasks with >3 similar executions
□ Check for threshold-based decisions using AI
□ Look for data formatting/processing done by AI
□ Find opportunities for incremental updates

Optimization Report Template:

markdown

## [Date] Token Optimization Report

### Findings
| Task | Current | Suggested | Savings |
|------|---------|-----------|---------|
| [Name] | AI every call | Script + cache | ~X% |

### Action Items
- [ ] [Task]: Convert to L0/L1/L2
- [ ] [Task]: Add caching layer
- [ ] [Task]: Implement incremental updates

Auto-trigger: Daily at configured time or manual via "检查token优化"

Installation

Step 1: Copy Templates (⚠️ Important: Copy to ROOT, not subfolders)

OpenClaw automatically loads these files from workspace root at session start:

CORE (required):

text

~/.openclaw/workspace/
├── AGENTS.md      ← Operation manual (auto-loaded)
├── SOUL.md        ← Agent principles (auto-loaded)
├── USER.md        ← User profile (auto-loaded)
└── MEMORY.md      ← Long-term memory (auto-loaded)

OPTIONAL (loaded if exists):

text

~/.openclaw/workspace/
├── IDENTITY.md    ← Agent identity (auto-loaded)
├── TOOLS.md       ← Environment tools (auto-loaded)
└── HEARTBEAT.md   ← Health check system (auto-loaded)

MEMORY templates (read on-demand):

text

~/.openclaw/workspace/memory/
├── learning-debt.md      (read via `read` tool)
├── constraints.md        (read via `read` tool)
├── preferences.md        (read via `read` tool)
└── token-audit-template.md  (read via `read` tool)

❌ WRONG - Do NOT do this:

bash

# Wrong - creates subfolders
mkdir -p ~/.openclaw/workspace/core
mkdir -p ~/.openclaw/workspace/assets
cp assets/* ~/.openclaw/workspace/core/  # ❌ WRONG

✅ CORRECT (or use install.sh):

bash

# Core templates → ROOT (auto-loaded by OpenClaw)
cp assets/AGENTS.md ~/.openclaw/workspace/
cp assets/SOUL.md ~/.openclaw/workspace/
cp assets/USER.md ~/.openclaw/workspace/
cp assets/MEMORY.md ~/.openclaw/workspace/

# Optional templates → ROOT (auto-loaded if exists)
cp assets/IDENTITY.md ~/.openclaw/workspace/
cp assets/TOOLS.md ~/.openclaw/workspace/
cp assets/HEARTBEAT.md ~/.openclaw/workspace/

# Memory templates → memory/ (read on-demand)
mkdir -p ~/.openclaw/workspace/memory
cp assets/learning-debt.md ~/.openclaw/workspace/memory/
cp assets/constraints.md ~/.openclaw/workspace/memory/
cp assets/preferences.md ~/.openclaw/workspace/memory/
cp assets/token-audit-template.md ~/.openclaw/workspace/memory/

# Note: BEST_PRACTICES.md stays in skill/assets/ (reference only, not auto-loaded)

Step 2: Configure User Profile

Edit ~/.openclaw/workspace/USER.md and fill in:

• Your name/role
• Communication preferences
• Technical level
• Constraints and boundaries

Step 3: Initialize Memory System

Create today's memory file:

bash

mkdir -p ~/.openclaw/workspace/memory
echo "# $(date +%Y-%m-%d) Memory Flush" > ~/.openclaw/workspace/memory/$(date +%Y-%m-%d).md

Step 4: Configure Weekly Token Audit (Auto-configured)

Token optimization audit is automatically configured during installation:

Default Schedule: Every Monday at 03:00 (cron)

text

0 3 * * 1 cd ~/.openclaw/workspace && echo '检查token优化' >> ~/.openclaw/workspace/.audit-trigger

Trigger methods:

1. Automatic - Runs every Monday 03:00 via cron
2. Manual - Say "检查token优化" anytime
3. Custom period - Say "检查本周token优化" or "检查本月token优化"

To change schedule, edit crontab:

bash

crontab -e
# Change: 0 3 * * 1 (Monday 03:00)
# To daily: 0 3 * * * (daily 03:00)
# To disable: Comment out or remove the line

File Reference

CORE Configuration (Auto-loaded by OpenClaw)

Must be in ~/.openclaw/workspace/ root.

File	Purpose	Key Content	Required
AGENTS.md	Operation manual	3-layer triggers, multi-expert, PUA levels	✅ Required
SOUL.md	Agent soul & principles	7 principles, PUA framework, safety rules	✅ Required
USER.md	User profile	Preferences, constraints, communication style	✅ Required
MEMORY.md	Long-term memory	High-signal info (Signal 8-10)	✅ Required

OPTIONAL Configuration (Auto-loaded if exists)

Placed in ~/.openclaw/workspace/ root. Loaded only if file exists.

File	Purpose	Key Content
IDENTITY.md	Agent identity	Display name, emoji, role definition
TOOLS.md	Environment tools	Local tool versions, API keys, commands
HEARTBEAT.md	Health check system	Quick status checks
TOKEN_AUDIT.md	Weekly audit config	Token optimization schedule, thresholds
CONFIG_CHECKLIST.md	Post-install verification	How to use all md files correctly

MEMORY Templates (Read on-demand)

Placed in ~/.openclaw/workspace/memory/. Read via read tool when needed.

File	Purpose
learning-debt.md	Topics to learn (Signal 6+)
constraints.md	Absolute boundaries
preferences.md	Preference change log
token-audit-template.md	Daily token optimization review template

Reference Documentation (Not auto-loaded)

Stay in skill/assets/. Read manually when needed.

File	Purpose
BEST_PRACTICES.md	Efficiency guide - Task layering, token optimization
README.md	This documentation

Quick Start

After installation, test the framework:

1. Test Layer 1 trigger:

   text

   用户: "这很重要，我偏好简洁的回答"
   Agent: [⭐] 已记录核心偏好: 简洁回答
   

2. Test Layer 2 trigger:

   text

   用户: "关键是配置要正确，别忘了备份"
   Agent: [⭐] 记录关键信息: 配置要正确
          [💾] 添加到学习债务: 别忘了备份
   

3. Test Multi-Expert mode:

   text

   用户: "多专家讨论: 如何设计一个高并发系统"
   Agent: [🧠 多专家模式]
          🔍 研究员: ...
          🧠 架构师: ...
          💻 工程师: ...
          👑 队长: ...
   

Updating

To update the framework while preserving your configurations:

1. Backup your USER.md and MEMORY.md
2. Reinstall the skill
3. Merge your custom configurations back

Resources

All templates are in assets/ directory:

• Core templates: SOUL.md, AGENTS.md, USER.md, MEMORY.md, HEARTBEAT.md
• Memory templates: learning-debt.md, constraints.md, preferences.md

Version

v3.2 - Task Layering & Cost Optimization