SKILLEMALL.ai

AD linkpix-seedance-2-clone

帮助抖音、TikTok、小红书短视频运营通过青虎AI完成“Seedance 2.0 爆款视频复刻”:通过识别热门视频的画面构图和节奏,利用Seedance 2.0的精准运动控制能力,一键复刻出具备高种草属性的商品短视频。适用于国内电商对标拆解、跨境电商热门趋势模仿、短视频批量起号等流程。能够精准处理复杂的镜头切换和动作连贯性,产出极具爆发力的社媒引流视频。 Use this skill for Seedance2.0爆款复刻, 爆款模仿, 热门视频拆解, 种草视频, 短视频起号, 抖音, TikTok, 小红书, 引流视频, 电商转化, AI视频复刻。通过青虎AI统一接入,支持视频分析、任务轮询和结果下载。 当用户要求用 Seedance 2.0 爆款视频复刻 或 Seedance 2.0 复刻/对标/照着做爆款视频时必须触发。关键词:LinkPix、qhkit、青虎、Seedance 2.0、爆款复刻、爆款模仿、热门视频拆解、种草视频、短视频起号、抖音、TikTok、小红书。

ClawHub Agent Skills author: AutoAGC v0.1.1 MIT-0 2 files body ≈ 1 583 tokens Open the sourceclawhub.ai analyzed 3 d ago

帮助抖音、TikTok、小红书短视频运营通过青虎AI完成“Seedance 2.0 爆款视频复刻”:通过识别热门视频的画面构图和节奏,利用Seedance…

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

ReferenceMarketingInfrastructuretype 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. 29 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1583 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 445: enough signal without eating the budget
    • +4Structure: 7 headings
    • +3Step-by-step instructions: 29 items
    • +4Has examples (4 code blocks)

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

    External checks

    ClawHub: suspicious
    The skill’s video-generation purpose is coherent, but it needs review because it asks the agent to install mutable third-party tools and handle a production API key through chat/commands.
    LLM: suspicious (high) · 8 Sept 2026