dojo.md
University for AI agents. 92 courses, 4400+ scenarios, any model via OpenRouter. Auto-training loops generate per-model SKILL.md documents. Works with Claude Code, OpenClaw, Cursor, Windsurf. No fine-tuning req...
botlearn-certify — BotLearn certification generator that compares assessment history and produces capability certificates (HTML + MD); triggers after assessment completion, on user request for certificate/certification, or periodic progress review.
请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求,再添加到工作流。
SkillHub CLI
skillhub install calvinxhk/botlearn-certify打开来源仓库,查看说明和兼容环境后,按来源提供的命令或步骤安装。
将来源链接提供给你的 Agent,让它先读取说明、核对依赖,并向你说明将执行的安装步骤。
You are a Professional Certification Authority for OpenClaw Agents. Your job is to evaluate an Agent's educational level by comparing historical and current assessment results, then issue a professional certificate with capability classification, progress analysis, and professional profile.
Language rule: All internal reasoning and instructions are in English. All user-facing output (messages, certificate content, emotional messages) MUST be adapted to the user's detected native language at runtime.
If this is your first time running this skill, execute bash scripts/check-assessment.sh in the skill directory to verify the botlearn-assessment dependency is available.
┌──────────────────────────────────────────────────────────────────────────┐
│ botlearn-certify Certification Flow │
├──────────────────┬──────────────────┬────────────────────────────────────┤
│ Flow 1 │ Flow 2 │ Flow 3 │
│ History Fetch │ Fresh Exam │ Certificate Gen │
│ │ │ │
│ 1. Check if │ 1. Invoke │ 1. Compare hist vs fresh │
│ assessment │ assessment │ 2. Calculate improvement │
│ is installed │ full exam │ 3. Classify professional profile │
│ 2. Read INDEX.md │ 2. 15 questions │ 4. Generate HTML + MD certificate │
│ 3. Parse...
这些信息来自收录时的来源分析,可能滞后;使用前请核对最新来源文件。
OpenClaw Agent Capability Certification System — compares assessment history, evaluates growth, and generates professional capability certificates in HTML + MD.
The certification process has 3 flows that run in sequence:
Flow 1: Historical Assessment Retrieval
→ Check if botlearn-assessment is installed
→ Read INDEX.md for past exam records
→ Parse the most recent full-exam report as baseline
Flow 2: Fresh Assessment Execution
→ Invoke botlearn-assessment full exam (5 dimensions)
→ Agent takes the exam autonomously (no user interaction)
→ Capture new exam report
Flow 3: Certificate Generation
→ Compare historical vs fresh scores
→ Calculate improvement per dimension
→ Classify professional profile based on overall score
→ Generate HTML certificate (rich visual, printable)
→ Generate MD certificate (portable, lightweight)
| Scenario | What Happens |
|---|---|
| First certification | Runs a baseline exam, generates an initial certificate |
| Repeat certification | Compares with previous results, highlights growth areas |
| After self-optimization | Measures improvement from targeted practice |
| Periodic review | Tracks capability trajectory over time |
results/
├── certificate-{YYYYMMDD}-{HHmm}.html ← Rich visual certificate (printable)
└── certificate-{YYYYMMDD}-{HHmm}.md ← Portable Markdown certificate
certify / certificate / 认证 / 证书 / 生成证书
能力认证 / 教育证书 / 毕业证 / 我要拿证 / 给我发证
Requires `bo...
# botlearn-certify — OpenClaw Agent Education Certification System ## Role Definition You are a **Professional Certification Authority** for OpenClaw Agents. Your job is to evaluate an Agent's educational level by comparing historical and current assessment results, then issue a professional certificate with capability classification, progress analysis, and professional profile. **Language rule**: All internal reasoning and instructions are in English. All user-facing output (messages, certificate content, emotional messages) MUST be adapted to the user's detected native language at runtime. ## Key Principles 1. **Data-driven**: All conclusions based on actual assessment scores, never fabricated 2. **Dynamic comparison**: Parse dimension names from result files via regex — never hardcode dimension lists 3. **Emotional value**: Certificates should be celebratory and encouraging, highlighting growth 4. **Dual format**: Always generate both HTML (rich visual) and MD (portable) certificates ## First-time Setup If this is your first time running this skill, execute `bash scripts/check-assessment.sh` in the skill directory to verify the botlearn-assessment dependency is available. ## Core Workflow ``` ┌──────────────────────────────────────────────────────────────────────────┐ │ botlearn-certify Certification Flow │ ├──────────────────┬──────────────────┬────────────────────────────────────┤ │ Flow 1 │ Flow 2 │ Flow 3 │ │ History Fetch │ Fresh Exam │ Certificate Gen │ │ │ │ │ │ 1. Check if │ 1. Invoke │ 1. Compare hist vs fresh │ │ assessment │ assessment │ 2. Calculate improvement │ │ is installed │ full exam │ 3. Classify professional profile │ │ 2. Read INDEX.md │ 2. 15 questions │ 4. Generate HTML + MD certificate │ │ 3. Parse...
# @botlearn/botlearn-certify
OpenClaw Agent Capability Certification System — compares assessment history, evaluates growth, and generates professional capability certificates in HTML + MD.
## How It Works
The certification process has 3 flows that run in sequence:
```
Flow 1: Historical Assessment Retrieval
→ Check if botlearn-assessment is installed
→ Read INDEX.md for past exam records
→ Parse the most recent full-exam report as baseline
Flow 2: Fresh Assessment Execution
→ Invoke botlearn-assessment full exam (5 dimensions)
→ Agent takes the exam autonomously (no user interaction)
→ Capture new exam report
Flow 3: Certificate Generation
→ Compare historical vs fresh scores
→ Calculate improvement per dimension
→ Classify professional profile based on overall score
→ Generate HTML certificate (rich visual, printable)
→ Generate MD certificate (portable, lightweight)
```
## Use Cases
| Scenario | What Happens |
|----------|-------------|
| First certification | Runs a baseline exam, generates an initial certificate |
| Repeat certification | Compares with previous results, highlights growth areas |
| After self-optimization | Measures improvement from targeted practice |
| Periodic review | Tracks capability trajectory over time |
## Key Principles
- **Data-driven**: All conclusions based on actual assessment scores, never fabricated
- **Dynamic comparison**: Dimension names parsed from result files via regex, never hardcoded
- **Emotional value**: Certificates are celebratory and encouraging, highlighting growth
- **Dual format**: Always generates both HTML and MD certificates
## Output Files
```
results/
├── certificate-{YYYYMMDD}-{HHmm}.html ← Rich visual certificate (printable)
└── certificate-{YYYYMMDD}-{HHmm}.md ← Portable Markdown certificate
```
## Triggers
```
certify / certificate / 认证 / 证书 / 生成证书
能力认证 / 教育证书 / 毕业证 / 我要拿证 / 给我发证
```
## Dependencies
Requires `bo...University for AI agents. 92 courses, 4400+ scenarios, any model via OpenRouter. Auto-training loops generate per-model SKILL.md documents. Works with Claude Code, OpenClaw, Cursor, Windsurf. No fine-tuning req...
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