Agent skill

Klingai Pricing Basics

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

Understand Kling AI pricing, credits, and cost optimization strategies.

MITAuto-check passedMedia & Creative

Install Klingai Pricing Basics

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

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

GitHub CLI
$ gh skill install jeremylongshore/tons-of-skills-marketplace klingai-pricing-basics --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-pricing-basics .claude/skills/klingai-pricing-basics && 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-pricing-basics
GitHub stars
2.8k
Token cost
~1.8k tokens
SKILL.md length
665 words
Files
6 (incl. references)
Skills in repo
3,342
Repo updated
First seen
Licence
MIT

At a glance

Understand Kling AI pricing, credits, and cost optimization strategies.

  • Works in 5 steps: Describe the workload and calculate the… → Run a single low-cost synthetic canary… → Require owner approval for the budget,… → …
  • Estimating costs
  • SKILL.md covers Overview, Subscription Plans (Web UI), Video Generation Costs and Image Generation Costs (Kolors), plus 10 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Klingai Pricing Basics is an agent skill from jeremylongshore/tons-of-skills-marketplace. Understand Kling AI pricing, credits, and cost optimization strategies. Use when budgeting or estimating costs. Trigger with phrases like 'kling ai pricing', 'klingai credits', 'kling ai cost', 'klingai budget'.

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/budget-management.md`, `references/cost-optimization-strategies.md` and `references/errors.md`). Compatibility notes: Designed for Claude Code

It sits in Media & Creative, covering AI video generation and Budgeting and forecasting. 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

  • Estimating costs
  • With phrases like kling ai pricing
  • Klingai credits

Example prompts

  • “kling ai pricing”
  • “klingai credits”
  • “kling ai cost”
  • “/klingai-pricing-basics”

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. Describe the workload and calculate the worst-case credits, including audio, retries, polling overhead where applicable, and a safety…
  2. Run a single low-cost synthetic canary through BudgetGuard. Confirm the selected model/mode and actual credit charge before authorizing…
  3. Require owner approval for the budget, destination, and promotion from draft/watermarked output to final delivery. Track actual credits by…
  4. Stop when a ceiling, policy check, rate limit, or cost anomaly fires. Cancel pending work where supported, remove quarantined outputs, and…
  5. At closeout, reconcile estimate versus actual, expire temporary artifacts and access, and retain a redacted cost receipt only.

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 Pricing Basics loads about 1.8k tokens when it runs, and up to ~3.5k if it reads all its reference files. Until then it costs about 59 tokens; SKILL.md has 665 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~59
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
~3.5k

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). 665 words, ~1,827 tokens.

Download SKILL.mdSave it as .claude/skills/klingai-pricing-basics/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.
name
klingai-pricing-basics
description
Understand Kling AI pricing, credits, and cost optimization strategies. Use when budgeting or estimating costs. Trigger with phrases like 'kling ai pricing', 'klingai credits', 'kling ai cost', 'klingai budget'.
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, pricing, cost-optimization

Kling AI Pricing Basics

Overview

Kling AI uses a credit-based pricing system. Credits are consumed per video/image generation based on duration, mode, and model. API pricing uses resource packs billed separately from subscription plans.

Subscription Plans (Web UI)

PlanMonthlyCredits/MonthKey Features
Free$066/day (no rollover)Basic access, watermarked
Standard$6.99660No watermark, standard models
Pro$25.993,000Priority queue, all models
Premier$64.998,000Professional mode, priority
Ultra$18026,000Max priority, all features

Warning: Paid credits expire at end of billing period. Unused credits do not roll over.

Video Generation Costs

DurationStandard ModeProfessional Mode
5 seconds10 credits35 credits
10 seconds20 credits70 credits
With Native Audio (v2.6)
DurationStandard + AudioProfessional + Audio
5 seconds50 credits100 credits
10 seconds100 credits200 credits

Image Generation Costs (Kolors)

FeatureCredits
Text-to-image1 credit/image
Image restyle2 credits/image
Virtual try-on5 credits/image

API Resource Packs

API access is billed separately from subscriptions via prepaid packs:

PackUnitsPriceValidity
Starter1,000~$14090 days
Growth10,000~$1,40090 days
Enterprise30,000~$4,20090 days

1 unit = 1 credit equivalent. API pricing works out to ~$0.07-0.14 per second of generated video.

Cost Estimation

python
def estimate_cost(videos: int, duration: int = 5, mode: str = "standard",
                  audio: bool = False) -> dict:
    """Estimate credits needed for a batch of videos."""
    base_credits = {
        (5, "standard"): 10,
        (5, "professional"): 35,
        (10, "standard"): 20,
        (10, "professional"): 70,
    }
    per_video = base_credits.get((duration, mode), 10)
    if audio:
        per_video *= 5  # audio multiplier

    total = videos * per_video
    return {
        "videos": videos,
        "credits_per_video": per_video,
        "total_credits": total,
        "estimated_cost_usd": total * 0.14,  # high estimate
    }

# Example: 100 five-second standard videos
print(estimate_cost(100, duration=5, mode="standard"))
# → {'videos': 100, 'credits_per_video': 10, 'total_credits': 1000, 'estimated_cost_usd': 140.0}

Cost Optimization Strategies

StrategySavingsTrade-off
Use standard mode for drafts3.5x cheaperSlightly lower quality
Use 5s duration, extend if needed2x cheaper per clipRequires extension step
Use kling-v2-5-turbo40% faster (less queue time)Marginally lower quality than v2.6
Batch during off-peak hoursFaster processingSchedule dependency
Skip audio, add in post5x cheaperExtra post-production step
Use callbacks instead of pollingNo cost savings, but fewer API callsRequires webhook endpoint

Budget Guard

python
class BudgetGuard:
    """Prevent overspending by tracking credit usage."""

    def __init__(self, daily_limit: int = 500):
        self.daily_limit = daily_limit
        self._used_today = 0

    def check(self, credits_needed: int) -> bool:
        if self._used_today + credits_needed > self.daily_limit:
            raise RuntimeError(
                f"Budget exceeded: {self._used_today + credits_needed} > {self.daily_limit}"
            )
        return True

    def record(self, credits_used: int):
        self._used_today += credits_used

Prerequisites

  • A named project, billing owner, approved daily and per-run credit ceilings, and a current provider pricing source. Treat the tables above as estimates until verified against the account's active plan or resource pack.
  • Define the model, duration, mode, audio setting, retry allowance, and expected failure rate. Use synthetic prompts and rights-cleared media for all estimation canaries; no real customer or personal data is needed.
  • Have a sandbox destination, draft/watermarked output policy, approval threshold, and a plan to cancel queued work and remove test outputs if the estimate is exceeded.
Show full SKILL.md (298 more words)Show less

Instructions

  1. Describe the workload and calculate the worst-case credits, including audio, retries, polling overhead where applicable, and a safety reserve. Check that the run fits both the project and account ceilings.
  2. Run a single low-cost synthetic canary through BudgetGuard. Confirm the selected model/mode and actual credit charge before authorizing the larger run.
  3. Require owner approval for the budget, destination, and promotion from draft/watermarked output to final delivery. Track actual credits by opaque run ID and aggregate model, not by prompt or media.
  4. Stop when a ceiling, policy check, rate limit, or cost anomaly fires. Cancel pending work where supported, remove quarantined outputs, and restore the approved lower-cost mode or last approved plan.
  5. At closeout, reconcile estimate versus actual, expire temporary artifacts and access, and retain a redacted cost receipt only.

Output

Return a budget worksheet or receipt with opaque run ID, pricing-source timestamp, model/mode/duration/audio assumptions, expected and maximum credits, reserve, actual credits, estimated currency range, approval state, canary result, destination class, retention deadline, and rollback/removal action. Exclude billing identifiers, prompts, media, user identities, and credentials.

Error Handling

  • If pricing or model parameters are stale or unknown, label the estimate provisional and stop before submission; do not infer a cheaper rate.
  • If credits are depleted or the charge exceeds the ceiling, pause the run and reconcile completed tasks before retrying. A policy refusal or rights failure is not a reason to retry.
  • If actual usage diverges from the estimate, quarantine outputs, cancel remaining tasks, notify the billing owner, and record the redacted variance and cleanup receipt.

Examples

For a synthetic 20-clip draft run, set duration=5, mode=standard, audio=false, credits_max=200, reserve=20%, destination=sandbox-review, and watermark=draft. Require approval=granted after the canary and actual_credits<=200; otherwise cancel pending tasks and remove the 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-pricing-basics of jeremylongshore/tons-of-skills-marketplace.

  • SKILL.md
  • references/budget-management.md
  • references/cost-optimization-strategies.md
  • references/errors.md
  • references/examples.md
  • references/pricing-structure.md

Open the folder on GitHubat commit cfae287

Compare with similar skills

Klingai Pricing Basics 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 Pricing Basics compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Klingai Pricing Basics this skilljeremylongshore/tons-of-skills-marketplace2.8k—~1.8kAutomated safety check: PassMIT
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Seedancesongguoxs/seedance-prompt-skill2.9k1 repos~2.5kAutomated safety check: PassNone

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Questions about Klingai Pricing Basics

What does Klingai Pricing Basics do?

Understand Kling AI pricing, credits, and cost optimization strategies. Klingai Pricing Basics is an agent skill from jeremylongshore/tons-of-skills-marketplace. Understand Kling AI pricing, credits, and cost optimization strategies.

When should I use Klingai Pricing Basics?

Klingai Pricing Basics fits situations like: estimating costs; with phrases like kling ai pricing; klingai credits.

How do I install Klingai Pricing Basics in Claude Code?

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

How do I install Klingai Pricing Basics in Codex?

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

Can I use Klingai Pricing Basics 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-pricing-basics -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-pricing-basics, .gemini/skills/klingai-pricing-basics, .github/skills/klingai-pricing-basics and .opencode/skills/klingai-pricing-basics in your project.

What does Klingai Pricing Basics need to run?

SKILL.md names no scripts, command-line tools or credentials: Klingai Pricing Basics 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 Pricing Basics 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 Pricing Basics 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 Pricing Basics use?

Klingai Pricing Basics 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 Pricing Basics use?

About 1.8k tokens (SKILL.md is roughly 7.3k 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 1.7k tokens, read only when the agent opens those files.

What are the alternatives to Klingai Pricing Basics?

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Who maintains Klingai Pricing Basics?

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.