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.
Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.
SkillHub CLI
skillhub install calvinxhk/botlearn-certifyInspect the source and compatibility requirements, then follow its installation steps.
Give your agent the source link and ask it to inspect instructions and dependencies before explaining the installation steps.
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...
These signals come from indexed source analysis and may lag behind changes. Check the current source files.
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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