Clone Ad

Clone ad — Seedance 2

Clone an existing video ad for a different product or offer. The agent analyzes the source video frame-by-frame, transcribes dialogue, extracts the visual style and beat structure, then generates a new Seedance 2 video (via KIE.ai) adapted for the user's product.

How this differs from analyze-video:

• analyze-video → output is a reusable markdown template saved to prompt-library/
• clone-ad → output is a generated Seedance 2 video delivered to the user

Prerequisites

Before starting, verify:

which ffmpeg || echo "MISSING — run: brew install ffmpeg"
python3 -c "import whisper; print('whisper OK')" 2>/dev/null || echo "MISSING — run: pip3 install openai-whisper"

Both extract-frames.sh and whisper depend on ffmpeg. If missing, install via brew install ffmpeg before proceeding.

Verify the exact Seedance model string on the KIE marketplace page. The likely value is seedance-2. Record the confirmed string in MASTER_CONTEXT.md.

Workflow

Step 0: Gather inputs

Collect from the user:

If the user only provides a video and says "clone this for my product," ask them for at least a product image URL or a text description before proceeding. Chat-pasted images do not count — KIE needs a real public URL.

Step 1: Extract frames and audio

Reuse the analyze-video extraction script — do NOT duplicate it.

bash "skills/kie-external-api/prompting/analyze-video/scripts/extract-frames.sh" \
  "<source_video_path>" "/tmp/clone-ad-analysis" <num_frames>

Frame count by duration:

Outputs:

• frame_001.jpg through frame_NNN.jpg
• audio.wav (16 kHz mono, whisper-ready)
• metadata.txt (duration, resolution, fps, frame count)

Read metadata.txt to get the source video duration — you'll need it for step 6.

Step 2: Transcribe audio

Use whisper to get the exact dialogue. This is critical — the dialogue pattern is what gets adapted for the user's product.

import whisper
model = whisper.load_model("base")
result = model.transcribe("/tmp/clone-ad-analysis/audio.wav")

Record:

• Full transcript text
• Per-segment timestamps and text (result["segments"])
• Total word count
• Language detected

If the video is silent (no speech detected), note that and skip the dialogue adaptation in step 7. The clone will be a visual-style clone only.

Step 3: Compressed analysis

Read ALL extracted frames visually. For each frame, note:

Structure and pacing:

• How many distinct beats/shots are there?
• What's the narrative arc? (hook → demo → verdict? reveal → detail → CTA?)
• How long does each beat last? (map to segment timestamps)

Camera and framing:

• POV style: selfie/handheld, tripod, propped phone, over-the-shoulder?
• Framing per beat: wide, medium, close-up, macro?
• Camera movement: static, pan, dolly, handheld shake?
• Signature framing moves (e.g., "leans into camera," "tilts product toward lens")

Edit style:

• Transition type: jump cuts, dissolves, match cuts?
• Visual rhythm: fast cuts vs held shots?
• Any recurring motif (e.g., "every other beat is an extreme close-up")?

Dialogue and script structure:

• Hook format: question, statement, exclamation, reaction?
• Speech pattern: casual/formal, filler words, trailing thoughts, mid-sentence cuts?
• How many spoken lines? How many silent beats?
• CTA style: direct ("link in bio"), soft ("you need to try this"), none?

Tone and energy:

• Emotion words that describe the speaker/mood
• Energy arc: starts calm → builds excitement? Flat? Burst then settle?
• Speaker's relationship to viewer: friend, expert, skeptic, fan?

Lighting and technical quality:

• Light source: natural/artificial, direction, quality
• Camera quality: phone/DSLR/cinema, intentional flaws?
• Audio quality: phone mic, studio, car, outdoor?

Product references:

• How is the product physically shown? (held up, worn, applied, on a surface)
• What specific claims or features are called out?
• Brand mentions, labels visible, text overlays?

What makes this ad distinctive (2–3 defining traits):

• The unique combination of elements that makes this ad recognizable
• These are the traits that MUST transfer to the clone

Store this analysis internally — it does NOT get saved as a template file.

Step 4: Present analysis summary

Show the user a structured breakdown before proceeding:

Source video analysis

Duration: Xs | Beats: N | Dialogue: Y words | Style: [style name]

Beat map:
  [00:00–00:03]  HOOK — close-up, excited expression, "opening line"
  [00:03–00:07]  SHOW — tilts product to camera, "feature call-out"
  [00:07–00:10]  DEMO — (silent) applies/uses product, close-up on texture
  [00:10–00:15]  VERDICT — back to camera, "closing line + CTA"

Defining traits:
  1. [trait 1]
  2. [trait 2]
  3. [trait 3]

What transfers to your product:
  - Beat structure, pacing, camera angles, edit style, tone, energy
  - Dialogue pattern (adapted for your product)
  - Lighting and technical quality cues

What gets swapped:
  - Product references → your product
  - Specific claims → your product's features
  - Brand mentions → your brand (if provided)

Proceed with adaptation? (yes / adjust)

Wait for user confirmation before continuing.

Step 5: Decide generation mode

Walk through this decision tree:

┌─ Source video ≤ 15s?
│   YES → Single-clip generation
│   NO  → Multi-clip split at natural beat boundaries
│         Each clip ≤ 15s (Seedance max)
│         Identify best split points from beat map
│         Use the CHAINED MULTI-CLIP PIPELINE below
│
├─ User provided a product IMAGE URL?
│   YES → Image-to-video mode (image URL in input.image_input; @(img1) in prompt)
│         For multi-clip: use the product URL on clip 1; for clips 2+, use the
│         previous clip's output frame or a re-upload (see chaining notes below).
│   NO  → Text-only mode (describe product in prompt text only; input.image_input omitted)
│
├─ Source video has person SPEAKING?
│   YES → Include dialogue in prompt text.
│         Dialogue confirmation gate REQUIRED (step 7)
│   NO  → Skip dialogue; visual-only prompt
│         Skip dialogue gate
│
└─ User wants voice clone from source audio?
    → On KIE's Seedance, native reference-audio support is unverified.
      Verify on the KIE marketplace page. If unavailable, note the limitation
      and proceed with text-driven dialogue only.

Chained multi-clip pipeline

When the source ad is longer than 15s, use this sequential pipeline for visual continuity:

Clip 1: image-to-video mode
  - input.image_input: ["https://.../product.jpg"]  ← establishes brand fidelity
  - Generate → poll → download output

Clip 2+: continuity mode
  - Option A (preferred): host the final frame of clip N as a public URL and pass
    it in input.image_input for clip N+1 to inherit hands/surface/lighting/product.
  - Option B: re-use the original product URL and lean on consistency anchors in
    the prompt ("The product from @(img1) must remain visually unchanged").
  - Generate → poll → download output

...continue for clips 3+

Critical rules for chaining:

1. Always chain from the most recent clip. Extract clip N's last frame with ffmpeg -sseof -0.1 -i clipN.mp4 -vframes 1 clipN_last.jpg, upload to your host, and pass the URL to clip N+1.
2. Wait for each clip to reach state: success before starting the next. Clips are sequential for continuity — do not fire in parallel.
3. Hosted URLs must stay reachable until generation completes. If using a temporary bucket, confirm expiry windows are longer than the job duration.
4. After all clips are generated, stitch with ffmpeg: ffmpeg -f concat -safe 0 -i list.txt -c copy output.mp4 (use absolute paths in the list file).

Why chaining works: Seedance-style continuity comes from carrying visual information (product, hands, surface, lighting) from clip N into clip N+1 via a reference image. The first clip's product URL establishes product identity; each subsequent clip's "last-frame-as-reference" propagates it through the series.

Cost note: Confirm per-second rates on the KIE marketplace page and record them in MASTER_CONTEXT.md. Log every job to logs/kie-api.jsonl so rates can be empirically verified from real runs.

Important constraints to check:

• KIE marketplace models use PUBLIC URLs in input.image_input — no file uploads.
• Up to 14 image URLs supported per job.
• Reference-video and reference-audio support on KIE's Seedance: verify on the marketplace page before planning around them. If unsupported, plan for image-reference + text-prompt workflows only.
• Content moderation: KIE runs its own safety checks. If a job fails moderation, credits may still be charged — rewrite the prompt rather than retrying the same payload.

Tell the user which mode you're using and why.

Step 6: Adapt for user's product

This is the creative core. Using the analysis from step 3:

Dialogue adaptation (if source has speech):

• Keep the same conversational pattern: if the source uses a question hook, use a question hook. If it uses filler words ("like," "okay so"), keep filler words.
• Keep the same number of spoken lines and same silent beat placement
• Keep the same energy arc (excited → calm, or flat, or building)
• Replace product-specific references with the user's product name, features, and claims
• Match the word count of each line closely (±3 words per beat) to preserve pacing
• Read the adapted dialogue out loud at natural pace — it must fit the target duration

Visual adaptation:

• Keep the analyzed camera work, framing per beat, and edit style
• Replace the product description with the user's product (physical appearance, colors, materials, label details)
• Keep the setting, lighting, and atmosphere
• Keep the person description (or adapt if user specifies a different persona)
• Keep the technical flaw cues (phone quality, mic type, lighting imperfections)

Prompt composition:

• Read seedance-2.md for platform rules before composing
• Read the closest matching style template (e.g., seedance-2-ugc.md for UGC-style sources) for structural guidance
• Follow the Subject + Action + Camera + Style + Constraints order
• Stay within 100–260 words (Seedance sweet spot)
• Include @(img1) token if user provided a product image URL
• Add consistency anchors: "The product from @(img1) must remain visually unchanged in every shot"
• Add pacing cues in the tone direction paragraph
• Use timestamps [00:00], [00:04], etc. for multi-beat sequences
• No forbidden words: cinematic, professional, stunning, 8k, studio, perfect

Duration selection:

• If source ≤ 15s: match source duration (or round to nearest second in 4–15 range)
• If source > 15s: split into clips, each ≤ 15s
• Use dialogue word count to validate (see main SKILL.md duration table: ~2.5 words/sec)

Step 7: Dialogue confirmation gate

MANDATORY for any clone with spoken dialogue. Follow the exact format from the main SKILL.md:

Dialogue script (please confirm before I generate)

  1. [HOOK]    "adapted line matching original pattern"
  2. [SHOW]    "adapted feature call-out for user's product"
  3. [DEMO]    (silent beat — physical demonstration, no dialogue)
  4. [VERDICT] "adapted closing line / CTA"

Total spoken words: ~N  |  Target duration: Xs  |  Fits at natural pace: yes/no

Approve this dialogue? (yes / edit / rewrite)

Rules:

• This gate is separate from the credit cost confirmation — both must be satisfied
• Never assume approval from earlier confirmations (tone, analysis, credit cost)
• If user says "edit" or proposes changes, revise and re-present until approved
• Skip ONLY if the source video is entirely silent (no speech detected in step 2)

Step 8: Audio decision

On KIE's Seedance, audio behavior is driven by what you write in the prompt (spoken lines are embedded in the prompt text). Native audio-toggle fields and reference-audio fields are marketplace-model-specific.

Ask the user:

1. Include dialogue in prompt? Default yes if the source has speech. Default no if the source is silent.
2. Voice cloning? Check the KIE marketplace page for the Seedance model to see whether it accepts reference audio inputs. If it does not, explain the limitation and proceed with text-driven dialogue. If it does, follow the field shape listed on the marketplace page (and record it in MASTER_CONTEXT.md).

Step 9: Credit cost estimation

Follow the main SKILL.md's mandatory estimation flow:

1. Check logs/kie-api.jsonl for matching model + similar config
2. Fall back to MASTER_CONTEXT.md rate table
3. For multi-clip: show per-clip and total
4. Present with source citation and estimate-only disclosure:

Estimated credit cost:
  Seedance 2 (15s i2v) × 1 clip × 1 variation = ~X credits
    (from logs/kie-api.jsonl YYYY-MM-DD)
  ─────────────────────────────────────
  Estimated total: ~X credits

  Estimate only — confirm exact cost in kie.ai/logs after the run.
  Proceed? (yes/no)

Do NOT generate until the user confirms.

Step 10: Prepare inputs

1. Confirm the product image URL is PUBLIC and reachable (curl -I returns 200).
2. If user supplied a local file, ask them to upload it to their host and share the URL.
3. If running in multi-clip mode, plan where clip N's last-frame URL will live.
4. Confirm KIE_API_KEY is loaded from .env.

Step 11: Generate

1. Compose the job body:

   {
     "model": "seedance-2",
     "callBackUrl": "",
     "input": {
       "prompt": "<composed prompt>",
       "image_input": ["<public product image URL>"],
       "aspect_ratio": "9:16",
       "duration": 15,
       "resolution": "720p",
       "output_format": "mp4"
     }
   }
   

   • aspect_ratio: match source video (9:16 or 16:9)
   • duration: from step 6
   • resolution: 720p (default)
   • Omit image_input entirely for text-only mode

2. Ask generation count (how many variations? default 1)

3. Single-clip: Fire N parallel POST https://api.kie.ai/api/v1/jobs/createTask calls. Multi-clip (chained): Fire clips sequentially per the chaining pipeline in step 5. Each clip depends on the previous clip's output — do not fire in parallel.

4. Log immediately to logs/kie-api.jsonl:

   {
     "timestamp": "...",
     "endpoint": "POST /api/v1/jobs/createTask",
     "model": "seedance-2",
     "taskId": "...",
     "request": { "duration": 15, "resolution": "720p", "aspect_ratio": "9:16" },
     "response": { "state": "queuing" },
     "notes": "clone-ad: ..."
   }
   

5. Poll GET https://api.kie.ai/api/v1/jobs/recordInfo?taskId=<taskId> until state is success or fail. Intermediate states: waiting, queuing, generating.

   • Single-clip: poll all variation taskIds concurrently
   • Multi-clip: poll each clip individually, wait for state: success before proceeding
   • Update log entry with final state, credit usage (from kie.ai/logs), wall-clock generation time, and the URLs parsed out of data.resultJson.

6. For multi-clip: extract clip N's last frame, host it at a public URL, pass it as input.image_input[0] for clip N+1.

Step 12: Present results

1. Save all videos to outputs/clone-ad-tests/ (or a descriptive subfolder)
2. Open the output folder on the user's machine so they can immediately review:

   open "outputs/clone-ad-tests/"   # macOS
   

3. Present watch/download URLs (parsed from data.resultJson).
4. For multiple variations: numbered list for comparison
5. For multi-clip:
   • Present each clip separately
   • Stitch with ffmpeg using absolute paths:

     printf "file '%s'\n" "$(pwd)/clip1.mp4" "$(pwd)/clip2.mp4" "$(pwd)/clip3.mp4" > /tmp/stitch-list.txt
     ffmpeg -y -f concat -safe 0 -i /tmp/stitch-list.txt -c copy stitched-output.mp4
     

   • Provide both stitched file and individual clips
6. Link to kie.ai/logs so the user can confirm the actual credit charge for each task.

Seedance 2 constraints (quick reference)

Check reference.md for full details. These are the ones most likely to bite during clone-ad:

Error recovery

Related files

• analyze-video/SKILL.md — the template-creation cousin (creates reusable .md templates instead of generating)
• analyze-video/scripts/extract-frames.sh — frame + audio extraction (reused by this skill)
• seedance-2.md — Seedance 2 platform rules (read before composing any prompt)
• seedance-2-ugc.md — 9-layer UGC formula (use as structural reference for UGC-style source videos)
• seedance-2-premium-reveal.md — premium reveal formula (for dark-void product-only source videos)
• seedance-2-product-hero.md — product hero formula (for elemental/effects product-only source videos)
• seedance-2-studio-lookbook.md — studio lookbook formula (for polished voiceover-style source videos)
• seedance-2-feature-walkthrough.md — feature walkthrough formula (for fast-paced demo source videos)
• ../../reference.md — API routes, job schemas, polling, constraints
• ../../SKILL.md — main execution checklist (dialogue gate, credit estimation, logging)