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starchild-ai-agent/official-skills2.4k installs

video

AI video generation: text-to-video, image-to-video, video-to-video, model selection. Use when generating a short video clip from a prompt or reference (e.g. 5s clip of a cat in rain, animate this photo, restyle this video).

How do I install this agent skill?

npx skills add https://github.com/starchild-ai-agent/official-skills --skill video
view source ↗

Is this agent skill safe to install?

  • Gen Agent Trust Hubfail

    The skill facilitates video generation and asset management but contains significant security vulnerabilities. Most notably, it is susceptible to path traversal, allowing arbitrary file writes. It also insecurely disables SSL verification for network requests and utilizes dynamic code execution for its internal operations.

  • Socketpass

    No alerts

  • Snykwarn

    Risk: MEDIUM · 1 issue

What does this agent skill do?

video

Use this skill for all video-generation requests on Starchild.

Core principle: call the provided scripts. Do not re-implement proxy/billing/upload plumbing.


1. Text-to-video (most common)

⚠️ Execution context — read this first. The code blocks below are Python, not shell commands. Starchild's bash tool runs /bin/bash -c, which cannot parse exec(open(...)) — pasting them directly into a bash command will fail with syntax error near unexpected token 'open'. Also, exec(open(...)) inside python3 -c fails with NameError: __file__ because the script uses __file__ for path resolution.

Use python3 - <<'EOF' with from exports import when calling via the bash tool:

python3 - <<'EOF'
import sys
sys.path.insert(0, "skills/video")
from generate_video import generate_video
result = generate_video(
    prompt="A cinematic drone shot over snowy mountains at sunrise",
    model="balanced",
    duration=5,
)
print(result)
EOF

The heredoc (<<'EOF') preserves all quotes and newlines — no escaping needed. Note: video skill has no exports.py — import directly from generate_video.

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/.

Delivering the result to the user — IMPORTANT

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:

  • Opening the link in a browser shows a blank page (no inline player triggered).
  • Embedding via <video> / <iframe> is blocked by CSP.
  • There is no Content-Disposition: attachment header, so the browser does not auto-download either.
  • URL-side tweaks (query params, ?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:

  1. Use result["local_path"] (e.g. output/videos/xxx.mp4) — generate_video always downloads on success.
  2. Tell the user the file is saved to output/videos/<filename> and is viewable in the workspace file panel / file browser.
  3. On Web channel, also embed it inline so the user can preview it in chat:
    ![video](output/videos/<filename>.mp4)
    
    (or link as [video](output/videos/<filename>.mp4) — the workspace serves these directly with the right headers).
  4. On Telegram / WeChat: send the file via 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.


2. Image-to-video / video-to-video (reference assets)

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.

Standard procedure

  1. Drop or copy the asset into output/fal_assets/ using publish_asset.py.
  2. Make sure a preview named fal-assets is running and published (one-time setup, see §3).
  3. Build the public URL as <preview_base>/<filename>.
  4. Call 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.

Asset constraints (enforced by publish_asset.py)

  • Image: .jpg .jpeg .png .webp .gif .bmp, max 10 MB
  • Video: .mp4 .mov .webm .mkv .m4v, max 100 MB
  • Anything outside these is rejected before publish

3. One-time fal-assets public preview setup

Run 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.


4. Model selection

TierModelCost / 5sNotes
budgetfal-ai/wan/v2.5/text-to-video$0.25Fastest, cheapest; good for prompt iteration
balancedalibaba/happy-horse/text-to-video$0.70Default; best lip-sync, most use cases
premiumbytedance/seedance-2.0/fast/text-to-video$1.20Best motion + camera direction
minibytedance/seedance-2.0/mini/text-to-video$0.36 (480p) / $0.77 (720p)Cheapest Seedance; resolution-tiered, no 1080p. Duration must be a string ("5", not 5 or "5s") — see gotcha below

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.


5. Polling an existing request

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.


6. Provided scripts

  • 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.

7. Troubleshooting

ProblemFix
image_url must be a public HTTP(S) URLUse 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 COMPLETEDReference asset host failed mid-render — re-encode/resize to 16:9, re-publish, retry
HTTP 402 insufficient_creditsTop up balance; cost is pre-charged on submit
HTTP 403 endpoint_not_allowedsc-proxy only allows approved fal video endpoints; pick one from the model table
Generation FAILED upstreamShorten prompt, drop unusual tokens, retry once before changing model
HTTP 422 literal_error on duration (Seedance Mini)Mini requires duration as a string ("5", "10", "auto"), not an int and not "5s". generate_video() encodes this automatically when model contains seedance-2.0/mini — only hit this if you hand-build the request body. Other Seedance variants accept int/"5s" as before.
Job stuck IN_PROGRESS >15 minSave 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).

8. Infrastructure (reference)

  • Caller → sc-proxyqueue.fal.run (and api.fal.ai) → fal model providers
  • All requests must include Authorization: Key fake-falai-key-12345 (proxy injects the real FAL_KEY)
  • Pre-charge happens at submit. Poll/result calls are free.
  • Allowed endpoints: video text-to-video / image-to-video / video-to-video / edit-video for the registered models. Anything else returns 403 endpoint_not_allowed.
  • Final mp4 lives at https://*.fal.media/... — public CDN, no auth needed for download.

9. Maintenance

  • Adding a new model → register price in generate_video.py::estimate_cost and in transparent-proxy/apis/falai.py::_VIDEO_PRICING.
  • Asset hosting via fal storage upload is intentionally not used in this skill: the production FAL_KEY lacks Serverless permission. Keep using the preview-based approach until that changes.

Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.

<a href="https://skillzs.dev/skills/starchild-ai-agent/official-skills/video">View video on skillZs</a>