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AD linkpix-minimax-h3-clone

帮助直播团队、带货达人通过青虎AI完成“MiniMax H3 爆款视频复刻”:将爆款视频中的话术、音色和情绪精准提取并重组,利用H3的多模态能力生成带原生情绪的带货视频。适用于批量生产抖音、小红书、视频号等高转化的素人种草测评视频,以及海外版TikTok的自动翻译配音复刻。不需要昂贵的中外配音和剪辑师,快速批量搭建账号矩阵,大幅降低爆款内容的边际生产成本。 Use this skill for MiniMaxH3爆款复刻, 爆款话术, AI配音, 素人种草, 矩阵起号, 抖音, 小红书, 视频号, TikTok, 多语言视频复刻, AI视频生成。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 MiniMax H3 爆款视频复刻 或 MiniMax H3 复刻/对标/照着做爆款视频时必须触发。关键词:LinkPix、qhkit、青虎、MiniMax H3、爆款话术、AI配音、素人种草、矩阵起号、多语言复刻、抖音、小红书、TikTok。

ClawHub Agent Skills author: AutoAGC v0.1.1 MIT-0 2 files body ≈ 1 579 tokens Open the sourceclawhub.ai analyzed 2 d ago

帮助直播团队、带货达人通过青虎AI完成“MiniMax H3…

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

ProcedureMarketingInfrastructuretype 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 1579 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 434: 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 asks users to share an API key in chat and directs agents to install mutable global dependencies, so users should review it before installing.
    LLM: suspicious (high) · 8 Sept 2026