/exercise-review.en
Lesson command
$ npx -y skills add minicoohei/ai-agent-camp --agent claude-codeHow it fires
How this command gets triggered: by you, by Claude, or both.
- Fires itselfClaude auto-loads it when your prompt matches the work.
- You can call itInvoke it directly when you want it.
- Slash command
/exercise-review.en
Context preview
What this command does when you run it.
Lesson command
Command definition
exercise-review.en.mddescription: "Lesson command"
nonInteractiveMode: compliant
Exercise Review
Usage
/exercise-review [exercise number] [output folder]
Examples:
/exercise-review 4-2 output/ex4-2
/exercise-review 7-3 ~/projects/gas-demo
Process
1. Deliverable Analysis
- Check files in the output folder
- Evaluate code quality
- Verify structure
2. Requirement Verification
Check each Module's exercise requirements and evaluate achievement:
- Fulfillment of mandatory requirements
- Implementation status of optional requirements
- Compliance with best practices
3. Improvement Feedback
- Code quality improvement suggestions
- Design pattern recommendations
- Security and performance considerations
4. Next Step Suggestions
- Additional topics to study
- Related practical exercises
- Expansion into real-world projects
Evaluation Criteria
Code Quality
| Item | Criteria | |------|----------| | Readability | Naming conventions, comments, structure | | Maintainability | Module separation, dependencies | | Testing | Coverage, edge cases | | Error Handling | Exception handling, log output |
Feature Fulfillment
| Level | Description | |-------|-------------| | A | All requirements met + additional features | | B | All mandatory requirements met | | C | Major requirements met | | D | Only some requirements met |
Output Format
## Exercise [number] Review Results
### Summary
- Overall Rating: [A/B/C/D]
- Completion: [XX%]
- Key Strengths:
- Areas for Improvement:
### Detailed Evaluation
#### Functional Requirements
| Requirement | Status | Comments |
|-------------|--------|----------|
| Requirement 1 | OK/NG | ... |
| Requirement 2 | OK/NG | ... |
#### Code Quality
- Readability: [X/5]
- Maintainability: [X/5]
- Testing: [X/5]
- Error Handling: [X/5]
### Improvement Suggestions
1. [Priority: High] ...
2. [Priority: Medium] ...
3. [Priority: Low] ...
### Next Steps
- Related exercises: start-X-X
- Reference materials: [URL]
Exercise List
Module 6: Agent Development
- 6-1: Commands creation
- 6-2: Skills creation
- 6-3: Best practices
- 6-4: Prompt engineering
- 6-5: Debugging
Module 7: Skill/Commands Creation
- 7-1 to 7-8: Skill/Commands practice
Module 8: Data Analysis
- 8-1: CSV/JSON processing
- 8-2: Database integration
- 8-3: API integration
- 8-4: Visualization
Module 9: Slack Integration
- 9-1: Slack MCP connection
- 9-2: Message automation
Module 10: GAS
- 10-1: Clasp basics
- 10-2: Calendar integration
- 10-3: Sheets integration
Module 11: GitHub Actions
- 11-1: Workflow creation
- 11-2: Secrets configuration
Module 12: Notion
- 12-1: MCP connection
- 12-2: DB operations
- 12-3 to 12-6: Notion CLI integration
Notes
- Error if the output folder does not exist
- Error if the exercise number is invalid
- Use review results as reference information
Read more
description: "Lesson command" nonInteractiveMode: compliant
Exercise Review
Usage
/exercise-review [exercise number] [output folder]
Examples:
/exercise-review 4-2 output/ex4-2 /exercise-review 7-3 ~/projects/gas-demo
Process
1. Deliverable Analysis
- Check files in the output folder
- Evaluate code quality
- Verify structure
2. Requirement Verification
Check each Module's exercise requirements and evaluate achievement:
- Fulfillment of mandatory requirements
- Implementation status of optional requirements
- Compliance with best practices
3. Improvement Feedback
- Code quality improvement suggestions
- Design pattern recommendations
- Security and performance considerations
4. Next Step Suggestions
- Additional topics to study
- Related practical exercises
- Expansion into real-world projects
Evaluation Criteria
Code Quality
| Item | Criteria | |------|----------| | Readability | Naming conventions, comments, structure | | Maintainability | Module separation, dependencies | | Testing | Coverage, edge cases | | Error Handling | Exception handling, log output |
Feature Fulfillment
| Level | Description | |-------|-------------| | A | All requirements met + additional features | | B | All mandatory requirements met | | C | Major requirements met | | D | Only some requirements met |
Output Format
## Exercise [number] Review Results ### Summary - Overall Rating: [A/B/C/D] - Completion: [XX%] - Key Strengths: - Areas for Improvement: ### Detailed Evaluation #### Functional Requirements | Requirement | Status | Comments | |-------------|--------|----------| | Requirement 1 | OK/NG | ... | | Requirement 2 | OK/NG | ... | #### Code Quality - Readability: [X/5] - Maintainability: [X/5] - Testing: [X/5] - Error Handling: [X/5] ### Improvement Suggestions 1. [Priority: High] ... 2. [Priority: Medium] ... 3. [Priority: Low] ... ### Next Steps - Related exercises: start-X-X - Reference materials: [URL]
Exercise List
Module 6: Agent Development
- 6-1: Commands creation
- 6-2: Skills creation
- 6-3: Best practices
- 6-4: Prompt engineering
- 6-5: Debugging
Module 7: Skill/Commands Creation
- 7-1 to 7-8: Skill/Commands practice
Module 8: Data Analysis
- 8-1: CSV/JSON processing
- 8-2: Database integration
- 8-3: API integration
- 8-4: Visualization
Module 9: Slack Integration
- 9-1: Slack MCP connection
- 9-2: Message automation
Module 10: GAS
- 10-1: Clasp basics
- 10-2: Calendar integration
- 10-3: Sheets integration
Module 11: GitHub Actions
- 11-1: Workflow creation
- 11-2: Secrets configuration
Module 12: Notion
- 12-1: MCP connection
- 12-2: DB operations
- 12-3 to 12-6: Notion CLI integration
Notes
- Error if the output folder does not exist
- Error if the exercise number is invalid
- Use review results as reference information
AI Agent Training for Non-Engineers - Complete Guide to Claude Code / Cursor / Codex ### ⚠️ Before you clone Official repository (maintained by the authors): Running AI agents from this repo grants them shell, file-write, and external-API permissions on your
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