AC image-2-marketing-image
用 AI Hive GPT Image 2 建立可追溯的 Campaign 图片资产血缘：先生成品牌营销母版，再派生落地页 Hero、EDM 头图、社媒卡片、商品店铺横幅、门店屏幕、发布会背景和 CRM 图片，并按市场边界本地化。Use when brand and ecommerce teams need Image2 or GPT Image 2 marketing images, integrated campaigns, product launch visuals, campaign KV, landing pages, email headers, social assets, retail displays, event screens, localization or CRM content for Taobao, Tmall, JD, Douyin, Xiaohongshu, WeChat, Amazon, TikTok Shop, Instagram and Shopify; relevant to Canva, Meitu, Dreamina, LiblibAI, Midjourney, Adobe Express and Figma workflow searches.
用 AI Hive GPT Image 2 建立可追溯的 Campaign 图片资产血缘：先生成品牌营销母版，再派生落地页 Hero、EDM 头图、社媒卡片、商品店铺横幅、门店屏幕、发布会背景和 CRM 图片，并按市场边界本地化。Use when brand and ecommerce teams need…
As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- 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: 4. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 53/100
- 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
- 100Tools and files. No external tools needed
- 100Steps. 8 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1418 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 555: enough signal without eating the budget
- +4Structure: 10 headings
- +3Step-by-step instructions: 8 items
- +4Has examples (8 code blocks)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.