AC kling-video
Generate, animate, and edit AI videos using Kuaishou's Kling 3.0 and Kling Video O3 — featuring cinematic motion quality, physics simulation, reference-based generation, and natural-language video editing. Supports text-to-video, image-to-video, reference-to-video, and video editing in Pro and Standard tiers, up to 1080p resolution, 3-15 second duration, with optional synchronized sound generation. Available via Atlas Cloud API at 15% off standard pricing. Use this skill whenever the user wants to generate AI videos, create video clips, animate images, edit existing videos, produce short films, make video content, or mentions Kling, Kuaishou video, KwaiVGI, or video generation/editing. Also trigger when users ask to create product demos, marketing videos, social media reels, animated scenes, cinematic clips, talking head videos, edit video content, remove objects from video, change video backgrounds, or any video content using AI.
As a process C 59/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice
How to improve
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 3. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- note
frontmatter-keyunknown frontmatter key "source" - note
frontmatter-keyunknown frontmatter key "homepage"
Process rating: all ten parameters 59/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 4 mutating operations with no state check
- 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 100Steps. 45 steps
- 100Failures and branches. 2 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3239 tokens
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +3Description length 944: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +4Structure: 30 headings
- +3Step-by-step instructions: 45 items
- +4Has examples (10 code blocks)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.