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digital-avatar-shopping-video

小省导购员多智能体数字人口播带货视频生成系统,以"小省导购员"为核心人设,打造专业购物助手+数字人口播带货视频一体化服务。涵盖五大智能体(小省导购员、带货脚本师、数字人口播生成师、带货画面设计师、音画合成师),产出"数字人口播+带货画面+字幕音效"的成品视频,适配抖音、快手等短视频平台,支持淘宝、京东、拼多多、唯品会等全平台商品信息,具备知识库自动存取能力。

60

Quality

68%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./skills/digital-avatar-shopping-video/digital-avatar-shopping-video/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

70%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The content is a well-structured multi-agent workflow with clear sequencing, validation checkpoints, and correctly signaled, real reference files. Its weaknesses are verbosity (repeated schemas and a duplicated trailing example block) and execution guidance that defers the hard parts to external references rather than providing complete, self-contained instructions.

Suggestions

Collapse the per-step JSON output schemas into a single shared template in a reference file and reference it, removing repeated inline blocks.

Remove or fix the duplicated trailing agent list in example 3 (the contradictory 120秒 '视频合成智能体' block) that conflicts with the example's 90秒 spec.

Replace vague execution cues ('使用图像生成能力生成视觉元素') with concrete, copy-paste-ready commands or minimal examples, or point explicitly to the specific reference section.

DimensionReasoningScore

Conciseness

The body is largely efficient with concrete specs, but it is heavily padded by repeated JSON output schemas and three full worked examples; example 3 even ends with a duplicated, contradictory leftover section (智能体3-5 re-listed with a 120秒 video that conflicts with the stated 90秒), so it could be tightened considerably.

2 / 3

Actionability

Concrete guidance is present (1080x1920 9:16 specs, BGM 25% volume, font choices, JSON templates, checklists), but the genuinely executable steps defer to references ('参考 references/tech-integration.md') or to vague abilities ('使用图像生成能力生成视觉元素'), leaving key execution details incomplete.

2 / 3

Workflow Clarity

The five-step closed-loop workflow is clearly sequenced with an explicit validation/checklist step (步骤5 校验归档) and a feedback loop (问题处理: 反馈对应智能体调整, 最多回溯2个层级), matching the rubric's anchor for clear sequences with validation and error-recovery.

3 / 3

Progressive Disclosure

A 资源索引 section signals one-level-deep references — agent-roles.md, workflow-steps.md, content-templates.md, tech-integration.md, and assets/examples/ — each accompanied by a '何时读取' cue, and all referenced paths resolve to real bundle files, giving clear navigation.

3 / 3

Total

10

/

12

Passed

Description

67%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description is specific and distinctive, clearly conveying a narrow vertical (digital-avatar shopping video generation across named platforms) in third person. Its main weakness is the absence of an explicit 'when to use' trigger clause and a tilt toward system jargon over natural user keywords.

Suggestions

Add an explicit trigger clause, e.g. '当用户需要生成带货视频、商品推荐视频、价格对比视频或购物咨询口播时使用'.

Lead with natural user-facing terms (带货视频、口播视频、商品推荐) before the multi-agent system description.

Trim the internal agent roster from the description; it inflates length without aiding triggering.

DimensionReasoningScore

Specificity

The description enumerates concrete capabilities — five named agents (小省导购员, 带货脚本师, 数字人口播生成师, 带货画面设计师, 音画合成师), a defined output (数字人口播+带货画面+字幕音效), and named target platforms (淘宝、京东、拼多多、唯品会) — listing multiple specific actions rather than vague claims.

3 / 3

Completeness

It clearly answers 'what' (generates digital-avatar shopping videos with the stated components and platforms) but provides no explicit 'when/Use when' trigger guidance, so per the rubric cap completeness stays at 2.

2 / 3

Trigger Term Quality

It contains relevant natural terms (带货视频, 短视频平台, 商品信息), but the phrasing is dominated by system-design jargon (多智能体, 数字人口播, 音画合成师) rather than the words a user would naturally say, and it omits common variations like 口播视频 or 商品推荐.

2 / 3

Distinctiveness Conflict Risk

The niche is sharply defined — a persona-driven digital-avatar live-shopping video generator tied to specific Chinese e-commerce platforms — making it unlikely to trigger for or conflict with unrelated skills.

3 / 3

Total

10

/

12

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
anbeime/skill
Reviewed

Table of Contents

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