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抖音 爆款带货视频生成。帮助抖音电商运营、直播团队、短视频创作者通过青虎AI完成“抖音 爆款带货视频生成”:可调用可灵Kling 3.0、阿里Wanx 3.0、MiniMax H3、Seedance 2.0、Seedance 2.5、HappyHorse 1.1等大模型,完美适配抖音前3秒抓人、快节奏、高完播率的算法特性。生成直播间切片、口播带货、剧情反转、好物测评、热点跟拍等视频类型,帮助店铺快速起号,大幅提升抖音商城及直播间的转化率。Use this skill for 抖音爆款视频, 短视频带货, 直播间切片, 口播带货, 剧情反转, 好物测评, 热点跟拍, 起号, 高转化率, 可灵Kling, 阿里Wanx, MiniMax H3, Seedance, AIGC视频生成。通过青虎AI统一接入,支持素材上传、任务轮询和结果下载。 当用户要求做抖音 爆款视频生成或抖音带货/种草/投放短视频时必须触发。关键词:LinkPix、qhkit、青虎、抖音爆款视频、抖音带货、直播间切片、口播带货、剧情反转、好物测评、热点跟拍、起号、抖音商城。

ClawHub Agent Skills author: AutoAGC v0.1.1 MIT-0 2 files body ≈ 1 536 tokens Open the sourceclawhub.ai analyzed 3 d ago

抖音 爆款带货视频生成。帮助抖音电商运营、直播团队、短视频创作者通过青虎AI完成“抖音 爆款带货视频生成”:可调用可灵Kling 3.0、阿里Wanx 3.0、MiniMax H3、Seedance 2.0、Seedance 2.5、HappyHorse…

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ReferenceMedia and videoInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
93/100
safety, quality, tests
Safety 60%
100
Quality 40%
83
Run on models
none yet
Process rating
D
46/100
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

    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: 2. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "homepage"

    Process rating: all ten parameters 46/100

    • 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
    • 60Tools and files. Uses tools (bash, python, node) that frontmatter does not declare
    • 100Steps. 25 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1536 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 475: enough signal without eating the budget
    • +4Structure: 7 headings
    • +3Step-by-step instructions: 25 items
    • +4Has examples (4 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 83.

    External checks

    ClawHub: suspicious
    This skill has a coherent video-generation purpose, but it tells the agent to install mutable third-party tools and collect an API key through chat, which users should review carefully before installing.
    LLM: suspicious (high) · 8 Sept 2026