How this report was made · admin only
Prompts are grouped by sport, then by pipeline step. Drag a prompt to reorder it within its step — the order is the sequence the AI reads them, and it changes the result.
API keys
Paste a key, it is checked with the provider, then stored in the engine's .env on this Mac.
Keys are write-only — they are never shown again. This admin page only works on the Mac running the engine.
AI engine
Gemini watches the whole clip — it does not just look at a few stills. The two knobs below do different jobs: the active one for your provider is bright, the other is dimmed.
Gemini (default): watches the full video at the rate on the left, then picks the coaching moments itself. The number of screenshots in the report is set by “Coaching screenshots” below, not here. Screenshot-only AIs (Claude, Qwen…): cannot watch video, so they only ever see the stills set on the right.
Add a provider
Any service that speaks the standard OpenAI-compatible API works: Qwen (DashScope), Doubao, DeepSeek, Kimi, OpenRouter, a local model… Enter the base URL (the part before /chat/completions). Added providers review sampled screenshots — only Gemini watches the whole video.
Report format (what the user receives)
Library storage
Off (default): the Library keeps the compressed video — cheap (~$0.02/mo per 100 reviews) and still fully watchable. On: keeps the original full-res upload.
Every analysis is saved here automatically. Sort and filter to find a past review.
Standard test set — the prompt regression loop
Flag a few pool clips as ★ standard, edit your prompts, then Generate to re-run them all and compare. Every run is saved to the Library, stamped with the exact prompt version that produced it — so you can see what an edit changed.
Compare runs each ★ clip on your current prompts only and pairs it with that clip's last saved run from the Library — so the old prompts aren't re-run (half the cost). Changes are highlighted.
Add a clip to the pool
Upload a clip once, re-analyze it any time without re-uploading. Stored durably on the engine.
Gold examples — teach the rubric
Build your evaluation form with any field types, then add videos with the expert answers filled in. Later the AI learns to reproduce these reports — the goal is ≥95% closeness to your gold.
Runs the AI on each gold video, fills your form, and scores how close it gets to your answers — field by field. Goal: ≥95%. ~2 AI calls per example (only when you click).