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Skillskie-gemini-omni

kie-gemini-omni

Design & creation

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Updated 10-15 19:57

About this skill

Kie Gemini Omni — image + video generation harness

You drive Kie AI's job queue (/api/v1/jobs/createTask + /api/v1/jobs/recordInfo) to produce images and short clips through Google's Gemini-family models. Veo3 is deprecated — use Nano Banana Pro for stills, gemini-omni-video for clips.

When to use which model

Use case Model ID Aspect / resolution Latency
DEFAULT — X-reply image, blog hero, brand visual, poster, diagram gpt-image-2-text-to-image (GPT Image v2, Anton's pick) aspect_ratio auto/16:9/1:1/9:16/… , resolution 1K/2K/4K 30-120 sec
Edit / restyle an existing image, or composite with reference images gpt-image-2-image-to-image same; pass refs via input_urls (public URLs) 30-120 sec
Fallback if GPT Image v2 errors or rejects the prompt nano-banana-pro (Gemini 3 Pro Image) 16:9, 1:1, 9:16 — 1080p/2K 10-30 sec
Cheap batch images (~20+ at once) nano-banana-2 (Gemini 3.1 Flash Image) same 5-15 sec
Short-form vertical clip 6-10s (TikTok/Reels/Shorts B-roll) gemini-omni-video 9:16, 16:9, 1:1, up to 10s 90-300 sec

Default still model is gpt-image-2-text-to-image (per Anton, 2026-06-01). It renders on-image text far more reliably than Nano Banana and is the right tool for posters/cards with words. Nano Banana Pro is the fallback only. Note the param differences vs Nano Banana: GPT Image v2 uses resolution: 1K|2K|4K (NOT 1080p), takes aspect_ratio (default auto; 1:1 cannot go 4K), and does NOT take output_format (returns PNG). Result still comes back as .data.resultJson → .resultUrls[0], same poller, same Cloudflare-UA download gotcha.

Never use Veo3 — Kie still exposes the endpoint for backwards compat, but the model is outdated, the prompts you'd write for Veo3 don't translate, and Gemini Omni Video produces equivalent or better output at lower credit cost.

Pre-flight (every run)

export KIE_API_KEY=$(security find-generic-password -s 'kie-api-key' -w 2>/dev/null || cat ~/.config/kie/api_key)
test -n "$KIE_API_KEY" || { echo "KIE_API_KEY missing"; exit 1; }

API key lookup order:

  1. KIE_API_KEY env var
  2. macOS Keychain kie-api-key
  3. ~/.config/kie/api_key
  4. Obsidian: 003 Resources/Technical Knowledge/Credentials-Secrets-Passwords/Kie creds.md

Pattern A — Image (GPT Image v2, default)

The single most common use. ~30-120 sec end-to-end.

Submit

TASK_ID=$(curl -sS -X POST https://api.kie.ai/api/v1/jobs/createTask \
  -H "Authorization: Bearer $KIE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-image-2-text-to-image",
    "input": {
      "prompt": "<your prompt — see prompt-craft section below>",
      "aspect_ratio": "16:9",
      "resolution": "2K"
    }
  }' | jq -r '.data.taskId')

echo "taskId=$TASK_ID"

aspect_ratio: auto (default) | 1:1 | 3:2 | 2:3 | 4:3 | 3:4 | 16:9 | 9:16 | 2:1 | 1:2 | 21:9 | … · resolution: 1K | 2K | 4K (1:1 cannot be 4K). No output_format field — returns PNG. Verified live 2026-06-01: returns 2048×1152 at 2K/16:9.

Image-to-image / edit / reference compositing — same endpoint, model gpt-image-2-image-to-image, add "input_urls": ["https://public-url/ref.png"] (must be public URLs, not local paths or data URIs):

  -d '{ "model":"gpt-image-2-image-to-image",
        "input": { "prompt":"<edit instruction>", "input_urls":["https://.../ref.png"], "aspect_ratio":"16:9", "resolution":"2K" } }'

Fallback model if GPT Image v2 errors twice or rejects the prompt — swap "model":"nano-banana-pro" and use "output_format":"png","resolution":"1080p" (Nano Banana uses 1080p/2K, NOT 1K/2K/4K).

For batches, send multiple createTask calls in parallel — Kie tolerates concurrent submissions per account.

Poll

poll_kie() {
  local tid=$1
  for i in $(seq 1 60); do
    resp=$(curl -sS "https://api.kie.ai/api/v1/jobs/recordInfo?taskId=$tid" \
      -H "Authorization: Bearer $KIE_API_KEY")
    state=$(echo "$resp" | jq -r '.data.state')
    case "$state" in
      success) echo "$resp" | jq -r '.data.resultJson' | jq -r '.resultUrls[0]'; return 0 ;;
      fail)    echo "$resp" >&2; return 1 ;;
      *)       sleep 3 ;;
    esac
  done
  echo "timeout" >&2; return 2
}

URL=$(poll_kie "$TASK_ID")
echo "Got: $URL"

Download (Cloudflare CDN gotcha)

Kie's tempfile.aiquickdraw.com CDN rejects the default Python-urllib/3.9 user agent with HTTP 403. Always force a Mozilla UA:

curl -sS -A 'Mozilla/5.0' -o ./image.png "$URL"

In Python:

import urllib.request
req = urllib.request.Request(url, headers={"User-Agent": "Mozilla/5.0"})
with urllib.request.urlopen(req) as r, open(out, "wb") as f:
    f.write(r.read())

Pattern B — Video (gemini-omni-video)

Use only for short-form B-roll, ad creative, social clips. 1-2 min latency per clip; submit-and-walk-away.

Submit

curl -sS -X POST https://api.kie.ai/api/v1/jobs/createTask \
  -H "Authorization: Bearer $KIE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gemini-omni-video",
    "input": {
      "prompt": "<prompt — see safe-prompts below>",
      "aspect_ratio": "9:16",
      "duration": 8,
      "image_urls": ["https://path/to/reference.png"]
    }
  }'
  • duration: requested values of 4 or 6 routinely come back as 8 or 10. Either pre-trim with ffmpeg or accept the longer clip.
  • image_urls: optional reference images. Up to 3-5. Pass real images (uploaded to your own CDN or Postiz, not data URIs).
  • Aspect: 9:16 for vertical (TikTok/Reels/Shorts), 16:9 for horizontal, 1:1 for IG square.

Poll + download

Same as Pattern A. Download via curl -A 'Mozilla/5.0'.

Failure modes (and how to recover)

Symptom Cause Fix
HTTP 500 on createTask (image OR video) Kie transient cluster error Retry up to 3x with same payload. ~30% of first-submissions on busy days return 500; the retry almost always succeeds. Credits are not charged on these.
state: fail with PUBLIC_ERROR_UNSAFE_GENERATION Safety filter rejected the prompt Rewrite, don't retry. Common triggers below.
state: fail with generic INTERNAL_ERROR Stochastic failure Retry up to 3x. Credits refunded.
Image downloads as 403 / empty Cloudflare CDN UA reject Use -A 'Mozilla/5.0'.
Image text is garbled Nano Banana Pro can produce bad typography under stress Pre-render text in a layer (Pillow/Sketch) and overlay yourself. Don't ask the model for fine typography in small font sizes.
Video duration is 8s when you asked for 4s Kie rounding Trim in post: ffmpeg -i in.mp4 -t 4 -c copy out.mp4. Or accept.

Safety filter triggers (avoid these in prompts)

Hard-learned from the 2026-05-22 JobWeave campaign:

  • Rejection-letter language: "we've decided to move forward with other candidates", "position has been filled". Use generic "status update" phrasing.
  • Competitor brand verbatim in body text: "Claude AI", "ChatGPT", "OpenAI", "Google" rendered as on-screen text. Filter is fine with these in non-rendered prompt sections; just don't ask the model to render the logo or product name.
  • Google OAuth modal flashes in screen recordings. Use a generic "sign-in modal" instead.
  • Lip-sync motion shorter than 3 seconds. Either render with motion-blurred lips, or no lip motion at all, or extend to ≥3s.
  • Identifiable people on video calls that the model would have to fabricate. Use blurred neutral avatars (initials over a soft colored circle) — preserves intent without the filter trigger.
  • Real CEOs / public figures by name when asked to render them visually. Generic descriptive prompts only.

The filter is intermittent. The SAME prompt can fail 3 times and succeed on attempt 4 unchanged. After 2 same-prompt fails, rewrite, don't keep retrying.

Prompt craft (Nano Banana Pro)

This model rewards specific, photoreal-cinematic prompts with clear composition. Pattern:

{Style}, {camera + lens}, {lighting + time of day}.
Subject: {2-3 sentences describing the central element with brand colors and aesthetic}.
Composition: {framing — close-up / wide / split-screen / panel}.
Text on image: {if any — keep to 1-2 short labels, large size, sans-serif, in quotes}.
Mood: {one adjective}.
Avoid: {anything you don't want}.

Example for an X reply on the spec-driven dev angle:

Vertical 16:9 photoreal cinematic, 35mm shallow depth of field. Cool blue-gray studio lighting.
Subject: A clean dark-mode terminal window centered in frame, showing 3 stacked spec files (spec.md, plan.md, tasks.md) with crisp purple syntax highlighting. The file titles are legible in white sans-serif.
Composition: tight centered framing, slight perspective tilt.
Text on image: A single white sans-serif label in the upper-third reading exactly "ship the spec, not the prompt."
Mood: confident.
Avoid: garbled text, third-party logos, generic stock aesthetics.

Prompt craft (gemini-omni-video)

10-second cap per clip. For longer videos, render multiple clips and concatenate.

Vertical 9:16 photoreal cinematic, {duration} seconds, shallow depth of field 85mm.
{Lighting + setting + time of day}.
{Subject description — keep continuity-friendly: same person, same outfit, same room across multi-clip sequences via image_urls references}.
{Action timeline using t=0s, t=2s, t=4s markers}.
{Text overlays — fixed sans-serif labels with exact quoted text}.
{Audio direction — "soft ambient room tone, no music" is the safest default}.
{Negative cues — "no garbled text, no recognizable third-party logos, photoreal skin"}.

Aspect-ratio cheat sheet

Platform Use Aspect Resolution to request
X reply / quote / blog hero image 16:9 1080p (= 1920×1080)
TikTok / Reels / Shorts image OR video 9:16 1080p (= 1080×1920)
Instagram feed image 1:1 OR 4:5 1080p
LinkedIn document image 1:1 OR 4:5 2K if doc-style
YouTube thumbnail image 16:9 2K (= 2560×1440)

Cost reference

Model Per-unit credits $ approx (assuming 1 credit ≈ $0.0007)
gpt-image-2-text-to-image (default) ~50-55 / image observed ~$0.04
gpt-image-2-image-to-image similar ~$0.04
nano-banana-pro (1080p PNG, fallback) ~60 ~$0.04
nano-banana-pro (2K PNG, fallback) ~120 ~$0.08
nano-banana-2 ~30 ~$0.02
gemini-omni-video (10s, 1080p) ~180 ~$0.13
gemini-omni-video (10s, 720p upscaled to 1080p) ~150 ~$0.10

Cost is not the constraint per Anton — pick the best model (GPT Image v2), not the cheapest.

Failures are not billed (Kie auto-refunds creditsConsumed on fail state).

Integration with the social engagement routine

The social-engagement-hourly scheduled task calls this skill on IMAGE_FIRE=1 fires (odd hours, ~8/day). Pattern: generate ONE 16:9 image for ONE of the 6-8 X replies, attach via the inline composer's file input, post. (The old twitter-social-media-promotion task is disabled — do not reference it.)

See ~/.claude/scheduled-tasks/social-engagement-hourly/SKILL.md Step 1.6.

Sample end-to-end (single image)

#!/usr/bin/env bash
set -euo pipefail
KEY=$(security find-generic-password -s 'kie-api-key' -w 2>/dev/null || cat ~/.config/kie/api_key)

PROMPT='Vertical 16:9 photoreal cinematic, 35mm shallow depth of field. Cool blue-gray studio lighting.
Subject: A clean dark-mode terminal window centered in frame, showing 3 stacked spec files (spec.md, plan.md, tasks.md) with crisp purple syntax highlighting. The file titles are legible in white sans-serif.
Composition: tight centered framing.
Text on image: A single white sans-serif label in the upper-third reading exactly "ship the spec, not the prompt."
Mood: confident.
Avoid: garbled text, third-party logos, generic stock aesthetics.'

TID=$(curl -sS -X POST https://api.kie.ai/api/v1/jobs/createTask \
  -H "Authorization: Bearer $KEY" -H "Content-Type: application/json" \
  -d "$(jq -n --arg p "$PROMPT" '{model:"gpt-image-2-text-to-image",input:{prompt:$p,aspect_ratio:"16:9",resolution:"2K"}}')" \
  | jq -r '.data.taskId')

echo "taskId=$TID, polling..."

for i in $(seq 1 60); do
  R=$(curl -sS "https://api.kie.ai/api/v1/jobs/recordInfo?taskId=$TID" -H "Authorization: Bearer $KEY")
  S=$(echo "$R" | jq -r '.data.state')
  case "$S" in
    success) URL=$(echo "$R" | jq -r '.data.resultJson' | jq -r '.resultUrls[0]'); break ;;
    fail) echo "$R" | jq '.data.failReason'; exit 1 ;;
    *) sleep 3 ;;
  esac
done

OUT=/tmp/kie-$(date +%s).png
curl -sS -A 'Mozilla/5.0' -o "$OUT" "$URL"
echo "Saved: $OUT"

Why this exists

Before this skill: every video/image gen run re-derived the model name from memory ("was it Veo 3.1 or gemini-omni-video?"), re-discovered the Cloudflare UA gotcha, re-tripped the safety filter on the same patterns, and used Veo3 by default — which is outdated and produces lower-fidelity results at higher credit cost. This skill locks in the model selection (Nano Banana Pro for images, Gemini Omni Video for clips), the safety-filter avoidance, the CDN UA, and the failure-recovery loop so every run starts from a known-good baseline.