SKILLEMALL.ai

AD linkpix-vidu-q2-sales

帮助电商商家、设计师和独立站运营通过青虎AI完成“Vidu Q2 电商带货视频”:Vidu Q2具备极其精准的参考图还原能力,支持超强的一致性生成,能完美复刻商品材质、纹路和包装细节。适配淘宝天猫服装SKU展示、拼多多饰品细节图动态化、1688产品演示、Amazon高档商品视频、Temu高质量广告素材、Shopee精细类目视频以及SHEIN独立站视觉营销。特别适合对材质还原要求极高的珠宝、服装、家具类目。 Use this skill for ViduQ2电商视频, AI视频生成, 商品一致性, 材质还原, 细节展示, 淘宝, 拼多多, 1688, Amazon, Temu, 独立站, 服装视频, 珠宝展示, 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。 当用户要求用 Vidu Q2 电商带货视频 或 Vidu Q2 做带货/商品/种草/广告视频时必须触发。关键词:LinkPix、qhkit、青虎、Vidu Q2、ViduQ2、商品一致性、材质还原、珠宝、服装、家具、淘宝、拼多多、Amazon、独立站。

ClawHub Agent Skills author: AutoAGC v0.1.1 MIT-0 2 files body ≈ 1 586 tokens Open the sourceclawhub.ai analyzed 3 d ago

帮助电商商家、设计师和独立站运营通过青虎AI完成“Vidu Q2 电商带货视频”:Vidu…

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

ProcedureInfrastructuretype 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. 28 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1586 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 473: enough signal without eating the budget
    • +4Structure: 7 headings
    • +3Step-by-step instructions: 28 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 matches its video-generation purpose, but it asks users to expose an API key in chat and directs agents to install or run mutable third-party packages with broad local effects.
    LLM: suspicious (high) · 8 Sept 2026