Video AI Direction

VerifiedCaution

AI video generation using the Kling API, covering prompt engineering, motion design, and platform specs for marketing content.

Sby Skills Guide Bot
ContentIntermediate
7/24/2026
Claude CodeCodex
#video-generation#kling-api#prompt-engineering#marketing#text-to-video

Recommended for

Automated summary

This skill directs marketing video generation through the Kling API: 8-element prompt construction, motion vocabulary, model selection, and text2video / image2video API calls.

Strengths

  • An 8-element prompt template (opening frame, motion, camera, lighting, mood, end frame) that is directly reusable
  • A deterministic Kling model selection table balancing quality, speed and use case (testing, ads, brand film)
  • Concrete per-platform specs (aspect ratio, duration, hook window) for TikTok, LinkedIn, Instagram, YouTube and X
  • Complete curl payloads for both text2video and image2video, including a standard negative prompt

Limitations

  • Assumes KLING_API_KEY and Kling API access are already set up
  • Does not cover the async polling loop, HTTP error handling or webhooks beyond the general idea
  • No guidance on editing, captions or text overlays, which it defers to post-production
When to use it

Use it when you need to write a Kling prompt and fire off a marketing video generation for a specific platform format.

When not to use it

Skip it if you are not using the Kling API, or if the task is video editing and post-production polish.

Security analysis

Caution
Quality score88/100

The skill instructs standard, transparent REST API usage: POST generation requests and poll for results against a documented Kling endpoint, authenticating with an env-var API key. No rm -rf, curl|sh, base64 payloads, or safety-disabling behavior. The only real risk is routine exposure of an API secret to an external host via Bash/curl, which warrants 'caution' rather than 'safe' or 'risky'.

Findings
  • •Uses Bash with curl to make network calls to an external API (https://api.klingai.com) — legitimate but requires trusting that endpoint.
  • •Sends $KLING_API_KEY as a Bearer token in request headers, transmitting a secret to a remote service. This is the normal/expected auth pattern, but the key must be scoped and the domain verified as the real Kling endpoint.
  • •Accepts image input as 'IMAGE_URL_OR_BASE64' — arbitrary URLs/base64 blobs could be forwarded to the third-party API; no validation guidance provided.
  • •Placeholders (FULL_PROMPT, TASK_ID, IMAGE_URL_OR_BASE64) are intended to be substituted before execution — no obfuscation, no destructive commands, no exfiltration to non-API hosts.
How this analysis is made

Examples

TikTok product teaser
Write a Kling prompt for a 5-second 9:16 TikTok ad for a matte black espresso machine, with a slow dolly in and golden hour lighting, then give me the curl command using kling-v1-5 in pro mode.
Animate a product photo
Use the video-ai-direction skill to turn this product image URL into a 5-second image2video clip with subtle product rotation for a LinkedIn ad.
Hero brand film prompt
Draft an 8-element Kling prompt for a hero brand film at 16:9 using kling-v2, aerial pull back over a coastal landscape, and include the negative prompt.

name: video-ai-direction description: AI video generation direction for Kling API — prompt engineering, motion design, platform specs, text-to-video and image-to-video workflows for marketing content allowed-tools: Read, Bash

Video AI Direction Skill

AI video generation using the Kling API (kling-v1-5 / kling-v2). This skill covers prompt construction, API workflow, platform specifications, and creative direction for marketing video content.

Kling API Architecture

Kling generates video asynchronously: you POST a generation request, receive a task ID, then poll until the video is ready.

Base URL: https://api.klingai.com/v1 Auth: Authorization: Bearer $KLING_API_KEY

Generation Modes

| Mode | Input | Best for | |------|-------|----------| | text2video | Text prompt | Campaign concepts, abstract, motion-first | | image2video | Static image + motion prompt | Product animation, photo-to-video |

Model Selection (Deterministic)

| Model | Quality | Speed | Use | |-------|---------|-------|-----| | kling-v1 | Good | Fastest | Testing, iterations | | kling-v1-5 | Better | Medium | Production ads (default) | | kling-v2 | Best | Slowest | Hero brand films |

Default for marketing: kling-v1-5 in pro mode.

Prompt Engineering

The 8-Element Prompt Structure

[OPENING_FRAME]: what the viewer sees in the first frame
[MOTION]: what moves, how it moves, camera behavior
[SUBJECT]: who/what is the protagonist
[STYLE]: cinematic / commercial / documentary / animated
[CAMERA]: static / dolly-in / pan / tilt / aerial / handheld
[LIGHTING]: natural / golden hour / studio / dramatic
[MOOD]: emotional register
[END_FRAME]: what the last frame holds

Negative prompt always includes:

blurry, distorted faces, watermark, text overlay, low quality, amateur, shaky, overexposed, artifacts

Motion Language Reference

Camera movements:

  • slow dolly in — intimate, focus draw
  • gentle pan right — reveal, storytelling
  • aerial overhead pull back — scale, context
  • static locked — stability, confidence
  • handheld slight movement — documentary authenticity
  • smooth tracking shot — following action

Subject motion:

  • subtle product rotation — product showcase
  • liquid pour in slow motion — food/beverage premium
  • hands interacting with [product] — demonstration
  • background bokeh shift — focus transitions
  • particle/dust float — atmosphere

Platform Specifications (Deterministic)

tiktok_reels:
  ratio: "9:16"
  duration: "5"      # 5s for ad, 10s for organic
  hook_window: "2s"
  key: mobile-first, native text overlays in post

linkedin:
  ratio: "16:9"
  duration: "5"
  hook_window: "3s"
  key: auto-plays muted, captions mandatory

instagram_feed:
  ratio: "1:1"
  duration: "5"
  hook_window: "2s"
  key: square for feed, 9:16 for reels

youtube_preroll:
  ratio: "16:9"
  duration: "5"      # skip at 5s, make it unskippable
  hook_window: "5s"
  key: must deliver value before skip

twitter_x:
  ratio: "16:9"
  duration: "5"
  hook_window: "2s"
  key: auto-plays muted

API Call Patterns

Text-to-Video

curl -s -X POST https://api.klingai.com/v1/videos/text2video \
  -H "Authorization: Bearer $KLING_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model_name": "kling-v1-5",
    "prompt": "FULL_PROMPT",
    "negative_prompt": "blurry, distorted faces, watermark, text overlay, low quality",
    "cfg_scale": 0.5,
    "mode": "pro",
    "aspect_ratio": "16:9",
    "duration": "5"
  }'

Image-to-Video (animate a static image)

curl -s -X POST https://api.klingai.com/v1/videos/image2video \
  -H "Authorization: Bearer $KLING_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model_name": "kling-v1-5",
    "image": "IMAGE_URL_OR_BASE64",
    "prompt": "MOTION_DESCRIPTION",
    "negative_prompt": "blurry, distorted faces, watermark, low quality",
    "cfg_scale": 0.5,
    "mode": "pro",
    "duration": "5"
  }'

Poll for Completion

# Poll every 15 seconds, up to 5 minutes
TASK_ID="<returned from generation call>"
curl -s https://api.klingai.com/v1/videos/text2video/$TASK_ID \
  -H "Authorization: Bearer $KLING_API_KEY"
# Check .data.task_status == "succeed" and extract .data.task_result.videos[0].url

Deliverable Structure

Every video brief produces 3 variants:

Variant 1 — Hero concept: Full prompt, primary creative vision Variant 2 — Hook variant: Different opening 2 seconds (stronger pattern interrupt) Variant 3 — CTA variant: Different ending (clearer or softer call-to-action frame)

Plus: script/caption copy for each variant (added in post via the video editor).

The 5-Second Rule

Every 5-second video must:

  • Second 1–2: Interrupt — something unexpected, beautiful, or emotionally resonant
  • Second 3–4: Communicate — one clear idea about the product or brand
  • Second 5: Direct — a visual that implies the next step (product logo, CTA frame)

No exceptions for ad placements. For organic content the same structure applies, with more room for story in seconds 3–4.

Common Rationalizations

| Rationalization | Reality | |---|---| | "I'll use std mode for speed" | std mode produces visibly lower quality. Always use pro for client assets. | | "The negative prompt isn't necessary" | Unguided generation consistently produces watermarks and text artifacts. Include it always. | | "One variant is enough" | The first generation is rarely the strongest. Three variants surfaces the best option and gives the client choice. | | "Platform ratio doesn't matter much" | Wrong ratio: 20–40% reach reduction on most platforms. Ratio is a technical requirement, not a preference. | | "I'll caption later" | Caption brief belongs in the deliverable now. Captions double engagement on muted auto-play. |

From the file to a first result

The download contains exactly the content displayed on this page. This copy may differ from the latest version in the source repository.

View the source and supporting files

This download contains SKILL.md only. Any scripts, references, templates and dependencies are not included. Get the required files from the source, preserving their directory structure, before continuing.

1. Download the file

Download SKILL.md

From the root of a test project, save the file as .skill-downloads/video-ai-direction-mryiqh4j/SKILL.md, or use the command below. This folder is for inspecting the skill before installation.

Command for macOS/Linux or WSL: requires a POSIX shell and curl. On Windows without WSL, use the download button and create the folder manually.

mkdir -p '.skill-downloads/video-ai-direction-mryiqh4j' && curl --fail --show-error --location 'https://skills-guides.com/api/skills/video-ai-direction-mryiqh4j/download' --output '.skill-downloads/video-ai-direction-mryiqh4j/SKILL.md.part' && mv '.skill-downloads/video-ai-direction-mryiqh4j/SKILL.md.part' '.skill-downloads/video-ai-direction-mryiqh4j/SKILL.md'

2. Check prerequisites

Read SKILL.md before using it. If it references scripts or external services, inspect them and prepare the required access in your test environment.

Tools declared by the author (check availability in your agent): Read, Bash

No recognized prerequisites section in this file. This does not mean it is self-contained: libraries, tools and access requirements may be mentioned elsewhere in the content or source repository.

The platforms on this page are catalog indications. The paths below follow tool documentation; they do not prove this skill has been run in those tools. No minimum tool version is confirmed for this listing.

3. Load the skill

After inspection, copy the complete folder into your project using one of the commands below, then open a new tool session. The command stops if a folder with the same name already exists: compare the files before replacing it.

Claude Code
test -f '.skill-downloads/video-ai-direction-mryiqh4j/SKILL.md' && test -s '.skill-downloads/video-ai-direction-mryiqh4j/SKILL.md' && mkdir -p '.claude/skills' && test ! -e '.claude/skills/video-ai-direction' && cp -R '.skill-downloads/video-ai-direction-mryiqh4j' '.claude/skills/video-ai-direction'

Codex
test -f '.skill-downloads/video-ai-direction-mryiqh4j/SKILL.md' && test -s '.skill-downloads/video-ai-direction-mryiqh4j/SKILL.md' && mkdir -p '.agents/skills' && test ! -e '.agents/skills/video-ai-direction' && cp -R '.skill-downloads/video-ai-direction-mryiqh4j' '.agents/skills/video-ai-direction'

OpenSkills

OpenSkills must already be installed. The local install/read procedure is checked with OpenSkills 1.5.0, which requires Node.js ≥ 20.6.0. Catalog slugs are not resolved automatically.

Official OpenSkills installation
openskills install './.skill-downloads/video-ai-direction-mryiqh4j'

openskills read 'video-ai-direction-mryiqh4j'

Reading should display the installed file content and its base directory. It does not run the skill or install its dependencies.

For an agent that reads AGENTS.md, then sync the index. This command changes AGENTS.md: review the diff before using it.

openskills sync

Manual method or another tool: attach SKILL.md to a conversation, or open it in an agent that can read files. Include any required supporting resources. No universal folder is recognized by every tool.

4. Try a first task

Use a short, synthetic input: an API endpoint, a small document or an interface brief. In a new conversation, attach the file or give the agent its path, then adapt this request:

Read .skill-downloads/video-ai-direction-mryiqh4j/SKILL.md and apply its instructions to this example: [describe a test input]. Identify any missing files, dependencies or access. Produce the result requested by the skill without inventing data or running unreviewed scripts.

Expected result: output matching the skill instructions, or a precise list of missing prerequisites. A read confirmation alone does not validate a first use. If an external resource is unavailable, that path remains untested.

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