AD mad-story
电影级影视分镜设计引擎，支持视频生成(Seedance 2.5默认/2.0降级/Runway/Kling/Sora)及图片生成(Seedream 4.x/5.x)。11种创作模式含短剧全链路。触发：影视分镜/分镜设计/电影分镜/广告分镜/电商视频/UGC广告/品牌短片/多镜头叙事/一镜到底/爆款复刻/短剧创作/AI视频生成/Seedance/Seedream/文生图/图生图/图像编辑/参考图生图/短剧剧本/微短剧/竖屏剧/AI短剧/锁脸/小说改短剧/漫剧/角色人设/时间戳控制/超长视频/视频延长/局部编辑/智能编辑/白模/绿幕/BGM分离/多语种/多宫格分镜。不适用于纯静态视觉设计或非分镜用途的通用AI绘画。
电影级影视分镜设计引擎，支持视频生成(Seedance 2.5默认/2.0降级/Runway/Kling/Sora)及图片生成(Seedream…
As a process D 49/100 · 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.
- 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: 18. 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") - note
frontmatter-keyunknown frontmatter key "modes" - note
frontmatter-keyunknown frontmatter key "phases" - note
frontmatter-keyunknown frontmatter key "references" - note
frontmatter-keyunknown frontmatter key "assets"
Process rating: all ten parameters 49/100
- 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
- 40Consistency. Frontmatter name (mad-story) differs from the folder (madstory)
- 100Tools and files. No external tools needed
- 100Steps. 35 steps
- 100Execution cost. Instruction body is 2678 tokens
- 100Running it twice. No mutating operations
- low 13 top-level sections: this looks like several domains in one skill
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
- +2Single-language instructions
- +3Description length 308: enough signal without eating the budget
- +4Structure: 25 headings
- +3Step-by-step instructions: 35 items
- +4Has examples (4 code blocks)
- +4Reference files are cited in the instructions (10 of 10)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.