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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。

56

Quality

63%

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

67%Weight 40%Scale 1-5

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

The body is a well-structured, actionable multi-agent workflow with concrete templates, specs, validation, and a feedback loop, supported by real one-level-deep reference files. Its main weakness is verbosity from repeated agent scaffolding and three exhaustive worked examples.

Suggestions

Trim the three worked examples to one representative end-to-end example and move the others into assets/examples/, where a full example-output.md already exists.

Move the per-agent 人设规范/音色语气 detail and full JSON output schemas into references/agent-roles.md and references/content-templates.md, keeping SKILL.md as an overview with compact field summaries.

Add explicit inter-agent handoff checkpoints (e.g. 'verify script_duration matches demand video_duration before口播生成') to make the validation between steps concrete rather than implicit.

DimensionReasoningScore

Conciseness

Mostly operational but noticeably verbose: the 5-agent section repeats an identical 职责/规范/输出格式 structure and three fully worked examples with exact prices and full scripts pad the document well beyond what Claude needs.

3 / 5

Actionability

Provides concrete per-agent JSON output templates and precise specs (1080x1920, 30fps, BGM 25%, 0.8x语速, 15秒≈30字) plus named tooling (Azure TTS, 百度TTS, FFmpeg, 剪映API, HeyGen, D-ID), with only minor gaps in executable detail.

4 / 5

Workflow Clarity

Clear 步骤1–5 sequence with a step-5 校验清单 and an explicit feedback loop ('迭代至达标…最多回溯2个层级'); validation is present, though some intermediate checkpoints between agents are implicit rather than spelled out.

4 / 5

Progressive Disclosure

A 资源索引 section points to four real reference files (agent-roles, workflow-steps, content-templates, tech-integration) and assets/examples/, each with '何时读取' guidance at one level deep, but the body still inlines substantial detail (full JSON schemas, persona norms) that could live in those references.

4 / 5

Total

15

/

20

Passed

Description

58%Weight 40%Scale 1-5

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 conveys a specific, well-scoped system with concrete capabilities, but is written as marketing prose rather than trigger-oriented guidance and omits an explicit 'Use when…' clause. Adding a concrete trigger clause and trimming promotional phrasing would lift specificity and completeness.

Suggestions

Append an explicit trigger clause, e.g. 'Use when the user asks to generate 带货视频, 口播 product recommendation videos, price-comparison videos, or shopping consultation videos for 抖音/快手.'

Replace marketing phrasing ('打造…一体化服务', '核心人设') with terse capability statements to improve specificity.

Surface the most natural user keywords ('带货视频', '口播', '商品推荐') earlier and drop jargon ('多智能体') from the description.

DimensionReasoningScore

Specificity

Lists several concrete actions and components (五大智能体, 数字人口播, 带货画面, 字幕音效, 全平台商品信息, 知识库自动存取), though padded with marketing phrasing like '打造专业购物助手+…一体化服务' that adds little.

4 / 5

Completeness

Clearly states what the system does, but lacks any 'Use when…' or equivalent explicit trigger guidance; per the rubric a missing trigger clause caps completeness at 3.

3 / 5

Trigger Term Quality

Contains relevant natural terms (带货视频, 口播, 抖音/快手, 短视频平台) but mixes in jargon ('多智能体', '数字人口播') and offers no explicit 'Use when…' trigger clause, leaving common user phrasings implicit.

3 / 5

Distinctiveness Conflict Risk

A highly specific named persona ('小省导购员') multi-agent带货视频 system occupies a clear niche with minimal overlap risk, though it could still brush against general short-video generation skills.

4 / 5

Total

14

/

20

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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