Kling 3.0 is a unified multimodal video model. It understands cinematic direction, not keyword lists. Write prompts like a director — describe what the audience sees, hears, and feels over time.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionkling-3-promptingExecute the skills CLI command in your project's root directory to begin installation:
Fetches kling-3-prompting from aedev-tools/kling-3-prompting-skill and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate kling-3-prompting. Access via /kling-3-prompting in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
2
total installs
2
this week
8
GitHub stars
0
upvotes
Run in your terminal
2
installs
2
this week
8
stars
Kling 3.0 is a unified multimodal video model. It understands cinematic direction, not keyword lists. Write prompts like a director — describe what the audience sees, hears, and feels over time.
Core shift: Description → Direction. Think "direct a scene" not "describe an image."
When invoked, guide the user through these steps using AskUserQuestion:
digraph builder {
"1. Generation mode?" [shape=diamond];
"Text-to-Video" [shape=box];
"Image-to-Video" [shape=box];
"Multi-Shot Sequence" [shape=box];
"Keyframe Transition" [shape=box];
"2. Gather scene details" [shape=box];
"3. Assemble prompt" [shape=box];
"4. Present & refine" [shape=box];
"1. Generation mode?" -> "Text-to-Video";
"1. Generation mode?" -> "Image-to-Video";
"1. Generation mode?" -> "Multi-Shot Sequence";
"1. Generation mode?" -> "Keyframe Transition";
"Text-to-Video" -> "2. Gather scene details";
"Image-to-Video" -> "2. Gather scene details";
"Multi-Shot Sequence" -> "2. Gather scene details";
"Keyframe Transition" -> "2. Gather scene details";
"2. Gather scene details" -> "3. Assemble prompt";
"3. Assemble prompt" -> "4. Present & refine";
}
Ask the user which mode:
Ask about each element (adapt questions to mode):
| Element | Question | Why it matters |
|---|---|---|
| Subject | Who/what is the focus? Specific appearance details? | Anchors consistency — define distinguishing traits early |
| Action | What happens? Describe the timeline (first → then → finally) | Kling 3.0 excels at sequential action over 15s arcs |
| Environment | Where? Be specific (not "a street" but "narrow Tokyo alley, steam from grates") | Grounds the scene physically |
| Camera | Shot type and movement? (See camera reference below) | Cinematic language produces far better results |
| Lighting | What light sources? Name them specifically | "Flickering neon" beats "dramatic lighting" |
| Mood/Emotion | What should the audience feel? | Drives color grade, pacing, music |
| Audio | Dialogue? Ambient sound? Music? | Kling 3.0 generates native audio + lip-sync |
| Duration | How long? (3-15s) | Longer = describe progression over time |
| Aspect Ratio | 16:9 / 9:16 / 1:1 / 21:9? | 16:9 cinematic, 9:16 social, 21:9 ultra-wide |
Image-to-Video: Focus on how the scene evolves from the image — movement, camera motion, environmental change. The model preserves identity/layout from the source.
Keyframes: Ask for start and end frame descriptions. Frames should match in color, style, and lighting. Prompt sparingly — Kling infers motion well.
Multi-Shot: Define each shot separately with its own framing, subject, action, and duration. Label shots explicitly.
Use the Master Formula:
[Scene/Environment] + [Subject & Appearance] + [Action Timeline] + [Camera Movement] + [Audio & Atmosphere] + [Technical Specs]
Writing rules:
Present the assembled prompt. Ask if they want to:
| Movement | Effect | Example phrase |
|---|---|---|
| Dolly push-in | Builds intimacy/tension | "slow dolly push-in toward her face" |
| Dolly zoom | Vertigo/dramatic reveal | "dolly zoom creating disorienting depth shift" |
| Tracking shot | Follows subject laterally | "camera tracks alongside as she walks" |
| Whip-pan | Energy/surprise | "whip-pan to reveal the door" |
| Crash zoom | Shock/emphasis | "sudden crash zoom on the object" |
| Rack focus | Shift attention | "rack focus from foreground hand to background figure" |
| Handheld/shoulder-cam | Raw/documentary feel | "handheld shoulder-cam with subtle sway" |
| Static tripod | Composed/observational | "locked-off static tripod, wide shot" |
| FPV drone | High-energy immersion | "dynamic FPV drone shot chasing through corridor" |
| Low-angle tracking | Heroic/imposing | "low-angle tracking shot, subject towers above" |
| Truck left/right | Lateral reveal | "camera trucks right revealing the cityscape" |
| Tilt up/down | Vertical reveal | "slow tilt up from boots to face" |
| Phrase | Effect |
|---|---|
| "Shot on 35mm film" | Warm grain, organic texture |
| "Macro 85mm lens" | Tight detail, shallow depth of field |
| "Wide-angle steadicam" | Smooth, immersive, spatial |
| "Handheld camcorder" | Raw VHS energy, nostalgic |
| "Anamorphic lens flare" | Cinematic horizontal streaks |
Use specific sources, not adjectives:
| Rule | Do | Don't |
|---|---|---|
| Name characters | [Character A: Silver-haired CEO] |
[Man] says... |
| Anchor to action | Agent slams table. [Agent, angrily]: "Where is it?" | Just dialogue without visual action |
| Assign voice tone | [CEO, deep authoritative gravelly voice] |
Generic "says" |
| Control timing | "Immediately," "Pause," "After a beat" | Back-to-back dialogue without transitions |
Shot 1 (0-5s): [Wide establishing shot description]
Shot 2 (5-10s): [Medium/close-up with action progression]
Shot 3 (10-15s): [Resolution/reaction with camera payoff]
Atmosphere: [Overall mood, color grade]
Audio: [Sound design, music, dialogue]
Label every shot. Assign durations. Describe framing + subject + motion per shot.
Use to prevent common AI defaults:
smiling, laughing, cartoonish, bright saturated colors, low resolution,
morphing, blurry text, disfigured hands, extra fingers, static pose,
frozen expression, stock photo aesthetic
Customize based on scene — remove items that conflict with your intent.
| Element | Weak | Strong |
|---|---|---|
| Camera | "Camera follows person" | "Handheld shoulder-cam drifts behind subject with subtle sway" |
| Subject | "A woman walking" | "Woman in red dress, heels clicking wet cobblestone" |
| Environment | "In a city" | "Narrow Tokyo alley, steam from grates, glowing vending machines" |
| Lighting | "Dramatic lighting" | "Flickering neon casting magenta/cyan across wet pavement" |
| Texture | "It looks realistic" | "Rain beading on leather jacket, condensation on glass, visible breath" |
| Motion | "She walks away" | "She turns slowly, hair catches light, disappears around corner" |
| Mistake | Fix |
|---|---|
| Keyword lists instead of scene direction | Write like directing a shot: subject + action + camera + environment |
| Vague motion ("moves," "goes") | Use cinematic verbs: dolly, track, whip-pan, crash zoom |
| Generic lighting ("dramatic") | Name the source: neon, candle, golden hour, LED panel |
| Overlong prompts | 1-3 rich sentences per shot; specificity > length |
| No temporal progression | Describe beginning → middle → end of the shot |
| Mismatched keyframes | Match color, lighting, and style between start/end frames |
| Unattributed dialogue | Label every speaker with name, tone, and emotion |
| Cramming multi-shot into one paragraph | Separate and label each shot with duration |
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
Keeps context tight: kling-3-prompting is the kind of skill you can hand to a new teammate without a long onboarding doc.
kling-3-prompting fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Registry listing for kling-3-prompting matched our evaluation — installs cleanly and behaves as described in the markdown.
kling-3-prompting reduced setup friction for our internal harness; good balance of opinion and flexibility.
We added kling-3-prompting from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Keeps context tight: kling-3-prompting is the kind of skill you can hand to a new teammate without a long onboarding doc.
kling-3-prompting is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
I recommend kling-3-prompting for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Useful defaults in kling-3-prompting — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
kling-3-prompting fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
showing 1-10 of 32