Agent skill

Klingai Model Catalog

by jeremylongshore in jeremylongshore/tons-of-skills-marketplace

Explore Kling AI models, versions, and capabilities for video and image generation.

MITAuto-check passedMedia & Creative

Install Klingai Model Catalog

skills CLI
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill klingai-model-catalog -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install jeremylongshore/tons-of-skills-marketplace klingai-model-catalog --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/.curated/klingai-model-catalog .claude/skills/klingai-model-catalog && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
klingai-model-catalog
GitHub stars
2.8k
Token cost
~1.8k tokens
SKILL.md length
654 words
Files
6 (incl. references)
Skills in repo
3,342
Repo updated
First seen
Licence
MIT

At a glance

Explore Kling AI models, versions, and capabilities for video and image generation.

  • Works in 5 steps: Translate the request into capability… → Eliminate unsupported or unapproved… → Compare aggregate quality, latency,… → …
  • Selecting models
  • SKILL.md covers Overview, Video Generation Models, Image Generation Models (Kolors) and Specialty Models, plus 10 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Klingai Model Catalog is an agent skill from jeremylongshore/tons-of-skills-marketplace. Explore Kling AI models, versions, and capabilities for video and image generation. Use when selecting models or comparing features. Trigger with phrases like 'kling ai models', 'klingai capabilities', 'kling video models', 'klingai features'.

Its SKILL.md is about 1.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including reference files (for example `references/available-models.md`, `references/errors.md` and `references/examples.md`). Compatibility notes: Designed for Claude Code

It sits in Media & Creative, covering AI video generation and Image generation. The repository describes itself as: Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com. The licence is MIT.

When your agent uses it

  • Selecting models
  • Comparing features
  • With phrases like kling ai models
  • Klingai capabilities

Example prompts

  • “kling ai models”
  • “klingai capabilities”
  • “kling video models”
  • “/klingai-model-catalog”

Requirements

  • Python 3
  • Compatibility (from SKILL.md): Designed for Claude Code
  • Pre-approved tools (allowed-tools): Read, Write, Edit, Bash(npm:*), Grep

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. Translate the request into capability requirements, then verify each candidate's current support, limits, pricing mode, and policy…
  2. Eliminate unsupported or unapproved candidates before generation. Run the smallest synthetic canary for the remaining candidates with…
  3. Compare aggregate quality, latency, credit use, policy result, and rights review. Choose the model that satisfies the requirements and…
  4. Obtain approval before production use. Keep the selected model ID pinned, monitor the first staged release, and revert to the approved…
  5. Remove rejected, superseded, or unapproved canary media, revoke temporary access, and retain a redacted selection receipt rather than raw…

What it can do on your machine

Read from SKILL.md and the folder at commit cfae287. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Write
    • Edit
    • Bash(npm:*)
    • Grep

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are python).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    Designed for Claude Code

    From compatibility in the SKILL.md frontmatter.

Context cost

Klingai Model Catalog loads about 1.8k tokens when it runs, and up to ~2.8k if it reads all its reference files. Until then it costs about 66 tokens; SKILL.md has 654 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~66
When it runs · the whole SKILL.md, loaded when a task matches
~1.8k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~2.8k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from jeremylongshore/tons-of-skills-marketplace at commit cfae287, republished under its MIT licence (© jeremylongshore). 654 words, ~1,794 tokens.

Download SKILL.mdSave it as .claude/skills/klingai-model-catalog/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.
name
klingai-model-catalog
description
Explore Kling AI models, versions, and capabilities for video and image generation. Use when selecting models or comparing features. Trigger with phrases like 'kling ai models', 'klingai capabilities', 'kling video models', 'klingai features'.
allowed-tools
Read, Write, Edit, Bash(npm:*), Grep
compatibility
Designed for Claude Code
version
1.18.0
license
MIT
author
Jeremy Longshore <jeremy@intentsolutions.io>
tags
saas, kling-ai, models, reference

Kling AI Model Catalog

Overview

Kling AI offers multiple model versions across video generation, image generation, lip sync, virtual try-on, and effects. Each version trades off quality, speed, and cost. This skill is the reference for choosing the right model.

Video Generation Models

Model IDSupportsMax DurationResolutionSpeedQuality
kling-v1T2V, I2V10s720pFastGood
kling-v1-5I2V only10s1080pFastBetter
kling-v1-6T2V, I2V10s1080pMediumBetter+
kling-v2-masterT2V, I2V10s1080pMediumHigh
kling-v2-1I2V only10s1080pMediumHigh
kling-v2-1-masterT2V, I2V10s1080pMediumHigh
kling-v2-5-turboT2V, I2V10s1080p 30fpsFastHigh
kling-v2-6T2V, I2V10s1080p 30-48fpsMediumHighest

T2V = text-to-video, I2V = image-to-video

  • 40% faster than v2.0
  • Up to 1080p at 30 FPS
  • Best cost/quality ratio for production pipelines
  • Native audio generation (voice, SFX, ambient in one pass)
  • 1080p at 30-48 FPS
  • Set motion_has_audio: true for synchronized audio

Image Generation Models (Kolors)

Model IDPurposeResolution
kolors-v1-5Face/subject referenceUp to 2048x2048
kolors-v2-0Image restyleUp to 2048x2048
kolors-v2-1Text-to-imageUp to 2048x2048

Specialty Models

FeatureEndpointModel Versions
Lip Sync/v1/videos/lip-syncv1.6+
Virtual Try-On/v1/images/kolors-virtual-try-onv1.5
Video Extension/v1/videos/video-extendAll video models
Effects/v1/videos/effectsv1.6+
Motion ControlT2V/I2V with camera_controlv1.6+

Mode Selection

Every video generation accepts a mode parameter:

ModeCredits (5s)Credits (10s)Use Case
standard1020Drafts, previews, iteration
professional3570Final output, client delivery

Model Selection Decision Tree

Need fastest generation?
  → kling-v2-5-turbo + standard mode

Need highest quality?
  → kling-v2-6 + professional mode

Need audio in the video?
  → kling-v2-6 with motion_has_audio: true

Image-to-video only?
  → kling-v2-1 (optimized for I2V)

Budget-conscious production?
  → kling-v2-5-turbo + standard mode (10 credits/5s)

Legacy compatibility?
  → kling-v1-6 (stable, well-documented)

API Usage

python
# Specify model in any video generation request
response = requests.post(f"{BASE}/videos/text2video", headers=headers, json={
    "model_name": "kling-v2-6",       # model version
    "mode": "professional",            # standard or professional
    "prompt": "A futuristic city at sunset with flying cars",
    "duration": "5",
    "aspect_ratio": "16:9",
})

Aspect Ratios (All Models)

RatioUse Case
16:9Landscape, YouTube, presentations
9:16Vertical, TikTok, Reels, Stories
1:1Square, Instagram, thumbnails
4:3Classic TV, presentations
3:4Portrait photos
3:2Standard photography
2:3Tall portrait
21:9Ultra-wide, cinematic

Prerequisites

  • A dated snapshot of the provider's current model and capability documentation, a selection owner, an approved credit budget, and an explicit fallback model.
  • Define the intended use, aspect ratio, duration, audio needs, quality/latency thresholds, and destination. Test with synthetic prompts and rights-cleared reference media only; confirm content-policy and likeness/consent requirements before submission.
  • Use a sandbox project and draft/watermarked canaries. Production promotion requires owner approval and a rollback/removal plan for outputs that fail policy, rights, quality, or cost checks.
Show full SKILL.md (291 more words)Show less

Instructions

  1. Translate the request into capability requirements, then verify each candidate's current support, limits, pricing mode, and policy constraints from the dated documentation snapshot.
  2. Eliminate unsupported or unapproved candidates before generation. Run the smallest synthetic canary for the remaining candidates with publish=false, watermark/draft enabled, and an explicit credit ceiling.
  3. Compare aggregate quality, latency, credit use, policy result, and rights review. Choose the model that satisfies the requirements and document why the fallback is acceptable.
  4. Obtain approval before production use. Keep the selected model ID pinned, monitor the first staged release, and revert to the approved fallback if any threshold or policy check regresses.
  5. Remove rejected, superseded, or unapproved canary media, revoke temporary access, and retain a redacted selection receipt rather than raw prompts or outputs.

Output

Return a model-selection record with requirements, documentation snapshot date, candidate IDs and exclusions, synthetic fixture ID, aggregate canary metrics, estimated credits, policy/rights outcomes, selected model, fallback, approval state, rollout scope, retention deadline, and rollback/removal reference. Do not include prompts, media, likenesses, audio, signed URLs, identities, or secrets.

Error Handling

  • If documentation is stale, contradictory, or missing a capability, mark the candidate unknown and stop selection until verified; do not guess from a model name.
  • If a candidate rejects content, lacks a required feature, exceeds budget, or fails quality/latency thresholds, quarantine and remove its canary output, then evaluate only an approved fallback.
  • If the selected model becomes unavailable or changes behavior, pause promotion, restore the pinned fallback, reconcile in-flight tasks, and record the redacted rollback receipt.

Examples

For a synthetic vertical draft, set requirements=t2v,9:16,5s, candidates kling-v2-5-turbo,kling-v2-6, destination=sandbox-review, watermark=draft, publish=false, and credits_max=100. Select only after policy=pass, rights=pass, and owner approval; otherwise remove both canary outputs.

Resources

© jeremylongshore, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 5 other files (references) in skills/.curated/klingai-model-catalog of jeremylongshore/tons-of-skills-marketplace.

  • SKILL.md
  • references/available-models.md
  • references/errors.md
  • references/examples.md
  • references/generation-types.md
  • references/model-selection-logic.md

Open the folder on GitHubat commit cfae287

Compare with similar skills

Klingai Model Catalog next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Klingai Model Catalog compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Klingai Model Catalog this skilljeremylongshore/tons-of-skills-marketplace2.8k—~1.8kAutomated safety check: PassMIT
SN Motion HTMLOpenSenseNova/SenseNova-Skills5.7k—~2.2kAutomated safety check: NotesMIT
Wedding Video Guided Wizardaaronyi97/wedding-video-guided-wizard310—~1kAutomated safety check: PassMIT
WorkrallyTencent/workrally166—~3.7kAutomated safety check: PassMIT-0
Gc Still Image Motion DirectorLiamGvchi/gc-still-image-motion-director152—~1.4kAutomated safety check: PassMIT
RunninghubHM-RunningHub/OpenClaw_RH_Skills142—~1.6kAutomated safety check: PassApache-2.0

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Questions about Klingai Model Catalog

What does Klingai Model Catalog do?

Explore Kling AI models, versions, and capabilities for video and image generation. Klingai Model Catalog is an agent skill from jeremylongshore/tons-of-skills-marketplace. Explore Kling AI models, versions, and capabilities for video and image generation.

When should I use Klingai Model Catalog?

Klingai Model Catalog fits situations like: selecting models; comparing features; with phrases like kling ai models; klingai capabilities.

How do I install Klingai Model Catalog in Claude Code?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill klingai-model-catalog -a claude-code`. Or copy the skill folder (skills/.curated/klingai-model-catalog in jeremylongshore/tons-of-skills-marketplace) into .claude/skills/klingai-model-catalog in your project. Claude Code loads it when a task matches its description.

How do I install Klingai Model Catalog in Codex?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill klingai-model-catalog -a codex`. Or copy the skill folder (skills/.curated/klingai-model-catalog in jeremylongshore/tons-of-skills-marketplace) into .agents/skills/klingai-model-catalog in your project. Codex loads it when a task matches its description.

Can I use Klingai Model Catalog in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill klingai-model-catalog -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/klingai-model-catalog, .gemini/skills/klingai-model-catalog, .github/skills/klingai-model-catalog and .opencode/skills/klingai-model-catalog in your project.

What does Klingai Model Catalog need to run?

SKILL.md names no scripts, command-line tools or credentials: Klingai Model Catalog is instructions for the agent only. Our summary lists: Python 3. Its frontmatter pre-approves these tools: Read, Write, Edit, Bash(npm:*), Grep. Compatibility (from SKILL.md): Designed for Claude Code.

Does Klingai Model Catalog access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Klingai Model Catalog safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Klingai Model Catalog use?

Klingai Model Catalog is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Klingai Model Catalog use?

About 1.8k tokens (SKILL.md is roughly 7.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1k tokens, read only when the agent opens those files.

What are the alternatives to Klingai Model Catalog?

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Who maintains Klingai Model Catalog?

jeremylongshore (a GitHub user) maintains it in jeremylongshore/tons-of-skills-marketplace, which has 2,827 GitHub stars. The repository holds 3,342 skills in this directory. The repository was last updated on October 10, 2026.

Source: jeremylongshore/tons-of-skills-marketplace on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.