BD aicraft-skill
爱创AI平台（www.51aic.com）电商AI内容创作助手。当用户有以下任何需求时，**必须**使用此技能： - 电商作图、商品图生成、主图套图、详情图制作 - AI生成图片、AI绘画、AI作图、Agent模式智能生成 - AI试衣、AI试鞋、AI试戴、虚拟试穿 - 商品精修、去水印、商品换色、服装去皱 - 图片翻译、商品替换背景、商品平铺图 - 换姿势、换表情、去牛皮癣/去除杂物 - AI视频生成、商品讲解视频、带货视频、短视频制作 - AI详情图生成、商品详情页、详情页规划 - 风格复刻、风格迁移、参考图风格生成 - 资产管理、素材管理、历史作品查看/下载/删除 - 提到"爱创"、"51aic"、"aicraft"、"大泽AI" - 任何需要上传图片进行AI处理/编辑/生成的电商场景 此技能帮助用户通过爱创AI平台的API完成图片生成、视频生成、图片编辑、详情图生成、风格复刻、资产管理等任务。 支持18种图片生成模式、AI视频生成、AI详情图生成、风格复刻和资产管理。
As a process D 47/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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: 5. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - warning
body-longSKILL.md body ≈ 7484 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 47/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 11 mutating operations with no state check
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (web, python) that frontmatter does not declare
- 70Execution cost. Instruction body is 7484 tokens
- 100Steps. 99 steps
- 100Consistency. Name and required fields are in place
- medium 8 test cases, all positive: not one "should refuse" or "should ask first"
- low No test case covers injection arriving through data
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 444: enough signal without eating the budget
- +4Structure: 36 headings
- +3Step-by-step instructions: 99 items
- +4Has examples (40 code blocks)
- +4Reference files are cited in the instructions (2 of 2)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 66.