SKILLEMALL.ai

AD linkpix-shopee-image

帮助Shopee卖家、东南亚电商运营通过青虎AI完成“Shopee商品图”:支持生成方形主图、促销贴纸图、白底图、买手秀风格图、多站点(不同语言)营销图。可调用Nano Banana 2 、GPT Image 2等大模型,生成迎合东南亚消费群体喜好、充满性价比与热销氛围的商品图。适用于Shopee、Shoppee Mall、Shopee Live等不同站点的商品视觉需求。Use this skill for Shopee商品图, 方形主图, 促销贴纸, 买手秀, 东南亚, 多语言, Nano Banana 2 , GPT Image 2, AIGC图像生成, 跨境电商。通过青虎AI统一接入,支持素材上传、实时模型配置、任务轮询和结果下载。 当用户要求做Shopee 商品图、主图套图、详情图、活动图生成或该平台的主图/套图/详情图/活动图时必须触发。关键词:LinkPix、qhkit、青虎、Shopee商品图、方形主图、促销贴纸、买手秀、Shopee Mall、Shopee Live、东南亚、多语言。

ClawHub Agent Skills author: AutoAGC v0.1.1 MIT-0 2 files body ≈ 1 534 tokens Open the sourceclawhub.ai analyzed 3 d ago

帮助Shopee卖家、东南亚电商运营通过青虎AI完成“Shopee商品图”:支持生成方形主图、促销贴纸图、白底图、买手秀风格图、多站点(不同语言)营销图。可调用Nano Banana 2 、GPT Image 2等大模型,生成迎合东南亚消费群体喜好、充满性价比与热销氛围的商品图。适用于Shopee、Shoppee…

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

ReferenceAI and agentsInfrastructuretype 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 1534 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 456: 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
    The skill is mostly coherent for Shopee image generation, but it asks users to send an API key in chat and installs mutable third-party command-line tooling.
    LLM: suspicious (high) · 8 Sept 2026