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xiaohongshu-makeup

自媒体创作者与电商运营在推广美妆护肤产品时,当需要创作或优化小红书笔记、生成AI配图提示词时,使用此技能可一键生成高转化爆款笔记、吸睛标题与精准标签,自动产出专业文生图提示词,轻松打造小红书爆款内容。

61

Quality

71%

Does it follow best practices?

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SecuritybySnyk

Passed

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Fix and improve this skill with Tessl

tessl review fix ./skills/xiaohongshu-makeup/xiaohongshu-makeup/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

65%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-organized, actionable overview that correctly delegates detailed templates to one-level-deep reference files. Its weak spots are redundancy between the generation and optimization flows and the lack of explicit validation gates in the workflows.

Suggestions

Consolidate shared guidance (标题, 正文, 标签 techniques) so the 笔记优化 flow references the generation flow instead of restating it, and trim the 使用示例 section to only illustrate what the steps do not already cover.

Add an explicit verification checkpoint at the end of each flow (e.g., '对照质量标准检查标题/正文/标签,不达标则返回修改') to turn the scattered checks into a clear validate-then-proceed gate.

DimensionReasoningScore

Conciseness

Mostly domain-specific actionable guidance without explaining known concepts, but the 笔记优化 flow largely mirrors the 笔记生成 flow and the 使用示例 section restates the steps, adding redundancy that could be tightened.

3 / 5

Actionability

Concrete, executable guidance for an instruction-only skill: explicit 正文结构 sub-sections, a 文生图 formula (主体+描述+场景+风格+细节+构图) with specific word banks, and a ready-made example title; the actual templates live in referenced files, leaving minor gaps in the body itself.

4 / 5

Workflow Clarity

Three clearly numbered multi-step flows are present, but validation checkpoints are implicit and scattered (a soft '优化笔记质量' check step, a separate 质量标准 section, 注意事项) rather than framed as explicit validate-then-proceed gates.

3 / 5

Progressive Disclosure

The body is a concise overview with a dedicated 资源索引 that signals each one-level-deep reference (note_templates.md, tag_library.md, image_prompt_guide.md, makeup_trends.md) along with its purpose; all referenced files exist in ./references/ and navigation is easy.

5 / 5

Total

15

/

20

Passed

Description

78%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 clearly communicates a distinct Xiaohongshu beauty-content niche with explicit trigger guidance and multiple concrete actions. Its main weakness is promotional padding ('爆款', '高转化', '轻松打造') that inflates the text without adding activation signal.

Suggestions

Trim marketing buzzwords ('高转化爆款', '轻松打造小红书爆款内容', '一键') so concrete capabilities and triggers stand out more clearly.

Add common user trigger terms like '种草' and '文案' alongside '笔记' to broaden natural keyword coverage.

DimensionReasoningScore

Specificity

Names several concrete actions ('创作或优化小红书笔记', '生成AI配图提示词', '一键生成...吸睛标题与精准标签', '自动产出专业文生图提示词'), but marketing fluff like '高转化爆款' and '轻松打造爆款内容' slightly dilutes the concrete coverage, keeping it just below a 5.

4 / 5

Completeness

Both 'what' (generate notes, titles, tags, image prompts) and 'when' ('当需要创作或优化小红书笔记、生成AI配图提示词时') are present and explicit, but the long marketing-laden sentence weakens the crispness of the trigger clause versus the clean 5 anchor.

4 / 5

Trigger Term Quality

Includes natural phrases users would say ('小红书笔记', '创作或优化笔记', 'AI配图提示词'/'文生图提示词', '美妆护肤') with synonym variation, but omits common Xiaohongshu terms like '种草' and '文案', so it is not a fully comprehensive 5.

4 / 5

Distinctiveness Conflict Risk

A clear, narrow niche (小红书 platform + 美妆护肤 domain) with platform-specific triggers ('小红书笔记', '文生图提示词') makes mis-activation for unrelated skills highly unlikely.

5 / 5

Total

17

/

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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