The AI-native design pipeline — concept to shipped MP4 in one workflow — step 7 of 8
Write score_pipeline(steps) that takes a list of step dicts and
returns an integer 0-100.
- Canonical step names:
["concept", "reference-gen", "composition", "audio", "captions", "render", "review"] - For each entry in
steps, count it as "covered" if BOTH:- its
stepfield is in the canonical list, AND - its
toolfield is a non-empty string.
- its
- Each unique canonical step covered = 15 points.
- Cap the score at 100.
- Return an
int.
Three teams run. Expected output:
team alpha: 100
team beta: 90
team gamma: 45
⌘↵ runs the editor.read, then continue.
Write score_pipeline(steps) that takes a list of step dicts and
returns an integer 0-100.
- Canonical step names:
["concept", "reference-gen", "composition", "audio", "captions", "render", "review"] - For each entry in
steps, count it as "covered" if BOTH:- its
stepfield is in the canonical list, AND - its
toolfield is a non-empty string.
- its
- Each unique canonical step covered = 15 points.
- Cap the score at 100.
- Return an
int.
Three teams run. Expected output:
team alpha: 100
team beta: 90
team gamma: 45
this step needs the editor
on desktop today; in the app (coming soon). save your spot and we'll bring you back here when you're ready.