SKILLEMALL.ai

AD kling-video

使用可灵 Omni-Video API 生成或编辑视频。凡是涉及可灵视频的操作都应触发此 skill,包括但不限于:可灵生成视频、kling视频、文生视频(可灵)、图生视频(可灵)、视频编辑(可灵)、视频参考。当用户明确提到"可灵"或"kling"并需要视频生成/编辑时触发。配置:环境变量 HSAI_API_KEY。

ClawHub Agent Skills author: gayyzxyx v1.0.0 MIT-0 3 files · 1 script body ≈ 665 tokens Open the sourceclawhub.ai analyzed 4 d ago

As a process D 41/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationMedia and videoInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
75
Run on models
none yet
Process rating
D
41/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
For the model run — optional
  • 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

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 41/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 40Consistency. Frontmatter name (kling-video) differs from the folder (kling-omni-video)
  • 60Tools and files. Uses tools (web) that frontmatter does not declare
  • 100Steps. 7 steps
  • 100Execution cost. Instruction body is 665 tokens
  • 100Running it twice. No mutating operations

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)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +3Description length 159: enough signal without eating the budget
  • +4Structure: 9 headings
  • +3Step-by-step instructions: 7 items
  • +4Has examples (5 code blocks)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.

External checks

ClawHub: clean
The skill appears to be a disclosed Kling video-generation integration, with the main caution being that it sends prompts and selected media files to a hosted API.
LLM: benign (medium) · VirusTotal: · 29 May 2026