AD avatar-outfit-motion-video
头像服装动作组合搭配视频——头像、服装、动作三必备主体要素 + 配音口播、背景、物品三可选次要要素，六要素皆可随机生成或指定（配音口播=音频驱动对口型、背景=场景生成/替换、物品=手持广告产品），走「判定→生成→组合→守护」五域管线：生成可独立交付、可自由组合的六要素资产，组合分固定组合（三视图锁身份、动作迁移/配音口播成片）与自由组合（任意要素→静态产物），提示词/产物双方式，输出 AI 换装/舞蹈/走秀/数字人口播/姿势短视频或静态资产。触发词：换装视频、AI 模特穿搭、虚拟试衣、动作迁移、音频对口型、配音口播、数字人、角色三视图、深度视频提取、背景替换、产品植入、手持道具、静态换装图、产品场景图、角色设定图、头像服装动作组合、meta-skill-system。
头像服装动作组合搭配视频——头像、服装、动作三必备主体要素 +…
As a process D 46/100 · 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: 26. 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")
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 (python) that frontmatter does not declare
- 100Steps. 47 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1750 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
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +3Description length 338: enough signal without eating the budget
- +4Structure: 29 headings
- +3Step-by-step instructions: 47 items
- +4Reference files are cited in the instructions (3 of 3)
- +3All 2 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.