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# Example workflow demonstrating per-step analysis configuration
# This workflow shows how to control when analysis runs
# Analysis always includes both metrics and context data
# First command: Implement a spec
# This uses the initial analysis from workflow start
- claude: "/prodigy-implement-spec $ARG"
commit_required: true
# No analysis configuration - uses initial context
# Second command: Run linting
# Linting typically doesn't need metrics data
- claude: "/prodigy-lint"
commit_required: false
# No analysis needed - works with existing code structure
# Third command: Code review
# This command benefits from fresh analysis
- analyze:
max_cache_age: 300 # Use cache if less than 5 minutes old
force_refresh: false # Don't force if cache is fresh
save: true
format: "summary"
- claude: "/prodigy-code-review"
# Fourth command: Clean up technical debt
# This needs fresh analysis to prioritize cleanup
- analyze:
force_refresh: true # Always get fresh analysis for accuracy
save: true
format: "summary"
- claude: "/prodigy-cleanup-tech-debt"
# Fifth command: Generate documentation
# This needs updated analysis after all changes
- analyze:
max_cache_age: 60 # Very short cache - 1 minute
force_refresh: false # Use cache if available and fresh
save: true
format: "summary"
- claude: "/prodigy-generate-docs"
# Usage examples:
#
# Run with a single spec:
# prodigy cook -p analysis-workflow.yml --args 45
#
# Run with multiple specs:
# prodigy cook -p analysis-workflow.yml --map "specs/*.md"
#
# Skip initial analysis (if commands have their own):
# prodigy cook -p analysis-workflow.yml --skip-analysis
#
# Force metrics for all commands:
# prodigy cook -p analysis-workflow.yml --metrics