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xiaohongshu-makeup

小红书美妆内容创作技能,支持笔记生成、笔记优化、文生图描述创作;适用于美妆护肤产品的内容创作、测评和营销推广

60

Quality

70%

Does it follow best practices?

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Adds up to 20 points to the overall score

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SecuritybySnyk

Passed

No findings from the security scan

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

Quality

Content

72%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 content is well-structured with good progressive disclosure to real reference files and concrete, actionable instruction-style guidance. The main gap is the absence of explicit validation checkpoints in the workflows.

Suggestions

Add explicit validation checkpoints to each flow, e.g., 'Before outputting the note: verify 10-15 tags, confirm no 绝对化用语/医疗功效 terms, and confirm title contains an emoji + 卖点'.

Tighten the '注意事项' section by merging overlapping items (真实性/避免敏感词/避免夸大) to reduce token cost.

Provide one fully worked end-to-end example (complete title + body + tag set) so the common case is copy-paste ready.

DimensionReasoningScore

Conciseness

The body is well-organized and mostly assumes Claude's competence (e.g., the prompt formula and word-bank pointers), with only minor trimmable padding in the '注意事项' and tone-style guidance; sits above the 3-anchor but not fully lean enough for a 5.

4 / 5

Actionability

Concrete, executable guidance for an instruction-only skill: numbered steps, a prompt formula ('主体 + 描述 + 场景 + 风格 + 细节 + 构图'), sample titles/tags, and word-bank references; only minor gaps prevent a 5.

4 / 5

Workflow Clarity

Three clearly numbered flows are sequenced, but checkpoints are implicit (e.g., '优化笔记质量' is a soft checklist rather than a hard validate-then-proceed step); the destructive/batch cap does not apply since this is content generation, but validation gaps remain at the 3-anchor.

3 / 5

Progressive Disclosure

A clear overview with a dedicated 资源索引 pointing one level deep to four real reference files via well-signaled markdown links with purpose annotations; bulk detail lives in the references, matching the 5-anchor.

5 / 5

Total

16

/

20

Passed

Description

67%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 conveys a specific niche and three concrete capabilities, with low conflict risk. Its main weakness is the absence of an explicit 'Use when...' trigger clause, relying instead on an applicability statement.

Suggestions

Replace the applicability phrase '适用于...' with an explicit 'Use when...' trigger clause, e.g., 'Use when the user asks for 小红书 美妆笔记 creation, optimization, or image-generation prompts'.

Add natural user-facing synonyms such as '种草', '推广文案', or '小红书配图' to broaden trigger-term coverage.

Spell out one concrete deliverable per capability (e.g., 'generates a complete note with title, body, and 10-15 tags') to lift specificity above 3.5.

DimensionReasoningScore

Specificity

Names the domain (小红书美妆) and three concrete actions ('笔记生成、笔记优化、文生图描述创作') plus an application area, sitting between the 3-anchor (1-2 actions) and 4-anchor (several specific actions) without fully detailing each action's deliverables.

3.5 / 5

Completeness

The 'what' is clear, but the trigger guidance is an applicability phrase ('适用于美妆护肤产品的内容创作...') rather than an explicit 'Use when...' clause, which per the rubric caps completeness at 3.

3 / 5

Trigger Term Quality

Includes natural domain terms like '小红书', '笔记生成', '笔记优化', '文生图', '美妆护肤', '测评', '营销推广' that users would plausibly say, with only minor natural synonyms (e.g., '种草', '推广文案') missing.

4 / 5

Distinctiveness Conflict Risk

A clear niche (小红书美妆 content) with domain-specific triggers that are unlikely to conflict with other skills.

5 / 5

Total

15.5

/

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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