Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub ยท Developer Tools
Nano Banana Kling Ad Workflow
Recreate low-budget AI video ad workflows using Nano Banana image generation plus Kling 3.0 video synthesis with dialogue, including prompt design, scene planning, cost control, and export handoff. Use when a user wants to produce a cinematic ad quickly (often in a few hours) with a small credit budget, or asks for a Deon-style Nano Banana + Kling pipeline.
skill openclawclawhub Free
Recreate low-budget AI video ad workflows using Nano Banana image generation plus Kling 3.0 video synthesis with dialogue, including prompt design, scene planning, cost control, and export handoff. Use when a user wants to produce a cinematic ad quickly (often in a few hours) with a small credit budget, or asks for a Deon-style Nano Banana + Kling pipeline.
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Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md, references/source-notes.md
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.0
Provenance
- Publisher
- gracelungu
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
Overview
Build a short ad from scratch using a fast two-stage pipeline: generate stills in Nano Banana, animate them in Kling 3.0, then stitch a publishable cut. Optimize for speed, visual consistency, and low spend.
1) Define outcome before generating assets
Capture these constraints first: Product or story concept Audience and tone Target duration (15s, 30s, or 45s) Delivery format (X, TikTok, Reels, YouTube) Budget ceiling in credits If missing, ask for only the minimum required details and proceed.
2) Build a shot list
Create 5-9 shots with: Shot number Scene goal Subject + environment Camera style On-screen line or dialogue intent Keep each shot prompt short and concrete.
3) Generate base visuals in Nano Banana
For each shot: Prompt for one clear hero frame Keep recurring anchors stable (character traits, wardrobe, color palette, lens style) Generate 2-4 variations max, pick one If consistency drifts, add explicit anchor text to the next prompt.
4) Animate in Kling 3.0
Import selected stills into Kling 3.0 and add: Motion direction (camera push, pan, dolly, parallax) Dialogue or narration intent Timing per clip (usually 2-5s) Prefer subtle motion over aggressive movement unless the concept requires action-heavy pacing.
5) Assemble final cut
Sequence clips by narrative flow: Hook (first 1-2 shots) Value demonstration Clear CTA Add captions if platform autoplay is likely muted.
6) Track cost and output quality
After generation, report: Total clips generated Credits used and estimated cost Final runtime Export ratio(s) What to improve in next iteration
Prompt pattern
Use this compact prompt shape for each Nano Banana shot: "[subject], [action], in [environment], [lighting], [camera framing], [style anchors], ultra-clean composition, ad-grade, no text overlays" Use this compact Kling prompt shape: "Animate this still with [motion], keep subject identity stable, cinematic realism, [timing], [dialogue/emotion cue], smooth transitions"
Fast defaults
Runtime target: 20-30 seconds Shot count: 6 Variations per shot: 3 Clip length: 3-4 seconds Revision passes: 1 content pass + 1 polish pass
Failure handling
If faces drift: repeat identity anchors and reduce motion complexity If scenes look noisy: simplify prompts and reduce style stacking If cost rises too fast: reduce variations and shorten shot list If timeline slips: ship a 15-second cut first, then extend
Deliverable format
When executing this skill, output: Final shot list Prompt set used Generation and edit log Final export summary Next-iteration recommendations
Category context
Code helpers, APIs, CLIs, browser automation, testing, and developer operations.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
2 Docs
- SKILL.md
- references/source-notes.md