Wraps fal.ai's video models for text-to-video, image-to-video, and video-to-video generation with three quality tiers (budget at $0.25/5s up to premium at $1.20/5s). The implementation handles a real gotcha: fal serves results with CSP headers that break browser playback, so the skill always downloads to local workspace files instead of handing users dead links. Image and video references need public URLs, which it solves by running a persistent preview server to expose assets. The polling and billing proxy logic is baked in so you just call generate_video() with a prompt and model tier. Solid if you need short AI clips without rebuilding the fal integration yourself.
npx -y skills add starchild-ai-agent/official-skills --skill video --agent claude-codeInstalls into .claude/skills of the current project.
Use this skill for all video-generation requests on Starchild.
Core principle: call the provided scripts. Do not re-implement proxy/billing/upload plumbing.
exec(open('skills/video/generate_video.py').read())
result = generate_video(
prompt="A cinematic drone shot over snowy mountains at sunrise",
model="balanced", # "budget" | "balanced" | "premium"
duration=5,
)
# result -> {"success": True, "cost": 0.70, "video_url": "...", "local_path": "output/videos/..."}
generate_video automatically: submits → polls → fetches result → downloads mp4 to output/videos/.
Never hand the user the raw video_url (e.g. https://*.fal.media/.../*.mp4). fal serves these files with Content-Security-Policy: sandbox; default-src 'none', which means:
<video> / <iframe> is blocked by CSP.Content-Disposition: attachment header, so the browser does not auto-download either.?download=1, etc.) cannot fix this — only a server-side header change would, and we don't control fal's CDN.The only reliable user-facing delivery path is the already-downloaded local file:
result["local_path"] (e.g. output/videos/xxx.mp4) — generate_video always downloads on success.output/videos/<filename> and is viewable in the workspace file panel / file browser.
(or link as [video](output/videos/<filename>.mp4) — the workspace serves these directly with the right headers).send_to_telegram(file_path="output/videos/...", message_type="video") or send_to_wechat(file_path="output/videos/...", message_type="video").If the download somehow failed (local_path missing) — re-fetch with:
curl -L -o output/videos/<filename>.mp4 "<video_url>"
Then deliver the local path. Still do not give the user the raw fal URL as the primary deliverable.
fal.ai needs the reference asset as a public https URL. fal storage upload requires a Serverless permission your key currently does not have. The reliable path is to expose the asset via a published Starchild preview.
output/fal_assets/ using publish_asset.py.fal-assets is running and published (one-time setup, see §3).<preview_base>/<filename>.generate_video(... image_url=public_url).# Step 1: publish a local image into the asset folder
exec(open('skills/video/publish_asset.py').read())
asset = publish_local('/path/to/your/photo.jpg')
# or: publish_from_url('https://example.com/photo.jpg')
filename = asset['filename']
# Step 2: combine with the preview's public base URL (see §3)
public_url = f"https://community.iamstarchild.com/<user_slug>-fal-assets/{filename}"
# Step 3: image-to-video
exec(open('skills/video/generate_video.py').read())
result = generate_video(
prompt="gentle cinematic camera push-in",
model="balanced",
duration=5,
image_url=public_url,
)
generate_video auto-rewrites the model path from */text-to-video to */image-to-video whenever image_url is provided. The same approach works for video-to-video models — pass an mp4 URL instead.
publish_asset.py).jpg .jpeg .png .webp .gif .bmp, max 10 MB.mp4 .mov .webm .mkv .m4v, max 100 MBfal-assets public preview setupRun this once per workspace. The preview keeps running across sessions.
# 3.1 ensure the asset folder exists with a placeholder index
import os, pathlib
pathlib.Path('output/fal_assets').mkdir(parents=True, exist_ok=True)
if not os.path.exists('output/fal_assets/index.html'):
open('output/fal_assets/index.html', 'w').write(
'<!doctype html><html><body><h1>fal asset host</h1></body></html>'
)
# 3.2 start the preview
preview(action='serve', dir='output/fal_assets', title='fal-assets')
# 3.3 publish to a public URL
preview(action='publish', preview_id='<id from step 3.2>', slug='fal-assets', title='fal-assets')
# → public base: https://community.iamstarchild.com/<user_slug>-fal-assets/
After publish, the public base URL is reusable for every future image-to-video / video-to-video task. Files dropped into output/fal_assets/ become reachable as <base>/<filename> immediately — no re-publish needed.
Verify with:
curl -sI https://community.iamstarchild.com/<user_slug>-fal-assets/<filename>
# expect: HTTP/2 200, content-type: image/* or video/*
If preview(action='serve') returns No available ports in pool, ask the user which existing preview can be stopped to free a port — never silently kill one.
| Tier | Model | Cost / 5s | Notes |
|---|---|---|---|
| budget | fal-ai/wan/v2.5/text-to-video | $0.25 | Fastest, cheapest; good for prompt iteration |
| balanced | alibaba/happy-horse/text-to-video | $0.70 | Default; best lip-sync, most use cases |
| premium | bytedance/seedance-2.0/fast/text-to-video | $1.20 | Best motion + camera direction |
Override by passing the full model id to generate_video(model=...). Image-to-video variants are auto-derived by replacing text-to-video with image-to-video.
Pricing details and model registry live in generate_video.py::estimate_cost.
exec(open('skills/video/poll_status.py').read())
result = poll_video("019ded6c-d871-7290-bbf1-ddc6993f8958")
Use this when an earlier generate_video call timed out or you only have a request_id.
generate_video.py — submit → poll → download. Handles text-to-video and image-to-video.publish_asset.py — copy local files (or download remote URLs) into output/fal_assets/ so they can be served by the fal-assets preview.poll_status.py — resume polling by request_id, downloads the result on completion.| Problem | Fix |
|---|---|
image_url must be a public HTTP(S) URL | Use publish_asset.py + fal-assets preview, then pass the public URL |
No available ports in pool (preview serve) | Ask the user which preview to stop; do not auto-kill |
downstream_service_error after COMPLETED | Reference asset host failed mid-render — re-encode/resize to 16:9, re-publish, retry |
HTTP 402 insufficient_credits | Top up balance; cost is pre-charged on submit |
HTTP 403 endpoint_not_allowed | sc-proxy only allows approved fal video endpoints; pick one from the model table |
Generation FAILED upstream | Shorten prompt, drop unusual tokens, retry once before changing model |
Job stuck IN_PROGRESS >15 min | Save request_id, resume later with poll_status.py |
| User reports the fal.media link "shows nothing" / "blank page" | Expected — fal serves with CSP: sandbox; default-src 'none'. Deliver the local file at result["local_path"] instead of the raw URL (see §1). |
sc-proxy → queue.fal.run (and api.fal.ai) → fal model providersAuthorization: Key fake-falai-key-12345 (proxy injects the real FAL_KEY)403 endpoint_not_allowed.https://*.fal.media/... — public CDN, no auth needed for download.generate_video.py::estimate_cost and in transparent-proxy/apis/falai.py::_VIDEO_PRICING.FAL_KEY lacks Serverless permission. Keep using the preview-based approach until that changes.sickn33/antigravity-awesome-skills
moizibnyousaf/ai-agent-skills
github/awesome-copilot