Generate Questions by Type

Generate IQ test questions of a specific type using the local question-service.

Usage

code

/generate-questions-by-type <type> [count] [difficulty]

Arguments

Argument	Required	Default	Description
`type`	Yes	-	Question type: `math`, `logic`, `pattern`, `spatial`, `verbal`, `memory`
`count`	No	50	Number of questions to generate
`difficulty`	No	all	Difficulty level: `easy`, `medium`, `hard`

Valid Question Types

•math - Mathematical reasoning and calculations
•logic - Logical deduction and reasoning
•pattern - Pattern recognition and sequences
•spatial - Spatial reasoning and visualization
•verbal - Verbal reasoning and language
•memory - Memory and recall tasks

Prerequisites

Before using this skill, ensure the following requirements are met:

•
Working Directory: This skill must be invoked from the repository root (the directory containing the question-service subdirectory). The cd question-service commands assume this directory structure.

•

Virtual Environment: The question-service virtual environment must be set up:

bash

cd question-service && python -m venv venv && source venv/bin/activate && pip install -r requirements.txt

•
Environment Variables: Required API keys must be configured in question-service/.env:
- •OPENAI_API_KEY - For question generation (Get an API key)
- •ANTHROPIC_API_KEY - For question judging (Get an API key)

Implementation

When this skill is invoked, follow these steps:

Step 1: Validate Arguments

Parse the arguments to extract type, count, and difficulty:

•If no arguments provided, show usage and exit
•Validate that type is one of: math, logic, pattern, spatial, verbal, memory
•If invalid type, show error with valid options and exit
•If count provided, validate it's a positive integer
•If difficulty provided, validate it's one of: easy, medium, hard

Step 2: Check Environment

Verify the question-service environment is ready:

bash

cd question-service && test -d venv && echo "venv exists" || echo "venv missing"

If venv is missing, inform the user they need to set up the question-service first.

Step 3: Execute Generation

Run the generation script with the validated parameters:

bash

cd question-service && source venv/bin/activate && python run_generation.py --types <type> --count <count> --async --async-judge --verbose

If difficulty is specified, note that the current run_generation.py script does not support a --difficulty flag. Inform the user that difficulty filtering is not yet implemented and proceed with generation of all difficulty levels.

Step 4: Report Results

After execution:

•Show the generation summary from the script output
•Report how many questions were generated and inserted
•Note any errors or warnings

Examples

Generate 50 math questions (default count)

code

/generate-questions-by-type math

Executes:

bash

cd question-service && source venv/bin/activate && python run_generation.py --types math --count 50 --async --async-judge --verbose

Generate 100 logic questions

code

/generate-questions-by-type logic 100

Executes:

bash

cd question-service && source venv/bin/activate && python run_generation.py --types logic --count 100 --async --async-judge --verbose

Generate 25 spatial questions (difficulty not yet supported)

code

/generate-questions-by-type spatial 25 hard

Notes that difficulty filtering is not yet supported, then executes:

bash

cd question-service && source venv/bin/activate && python run_generation.py --types spatial --count 25 --async --async-judge --verbose

Error Handling

Invalid Type

code

Error: Invalid question type 'foo'.
Valid types: math, logic, pattern, spatial, verbal, memory

Invalid Count

code

Error: Count must be a positive integer. Got: 'abc'

Missing venv

code

Error: Question service virtual environment not found.
Please run: cd question-service && python -m venv venv && source venv/bin/activate && pip install -r requirements.txt

Exit Code Handling

The run_generation.py script returns exit codes that indicate the result. Handle each exit code as follows:

Exit Code	Meaning	Action
0	Success	Report the number of questions generated and inserted. No action needed.
1	Partial failure	Some questions were generated but others failed. Report the count of successful insertions and warn the user to check logs at `question-service/logs/` for details on failures. Suggest retrying with a smaller count if many failures occurred.
2	Complete failure	No questions were generated. Check the error output for the cause. Common causes: API rate limits, network issues, or invalid prompts. Suggest the user wait and retry, or check API quotas.
3	Configuration error	Environment or argument configuration is invalid. Check that `.env` file exists with valid API keys. Verify all required environment variables are set.
4	Database error	Cannot connect to or write to the database. Verify database connectivity and check database configuration (`DATABASE_URL`). For local SQLite, ensure `question-service/questions.db` exists and is writable.

Example handling:

bash

cd question-service && source venv/bin/activate && python run_generation.py --types math --count 50 --async --async-judge --verbose
EXIT_CODE=$?

case $EXIT_CODE in
  0) echo "Generation completed successfully." ;;
  1) echo "Partial failure. Check logs at question-service/logs/ for details." ;;
  2) echo "Complete failure. Check API quotas and retry." ;;
  3) echo "Configuration error. Verify .env file and environment variables." ;;
  4) echo "Database error. Check database file permissions and connectivity." ;;
esac

Notes

•This skill runs generation locally using the question-service in your dev environment
•For production generation, use /generate-questions which triggers the Railway service
•Generation uses async mode for improved performance
•Questions are judged and deduplicated before insertion
•Check question-service/logs/ for detailed logs after generation