.claude/skills/ux-feedback-analyzerRuntime, accounts, dependencies, permissions, network behavior and task quality remain untested.
用户反馈情感与痛点分析助手。批量分析用户评论、问卷开放题,做情感极性判断与痛点分类,输出设计评审洞察。
These states come from the source or distribution context. None of the entries below are SkillVetAI compatibility test results.
These checks parse the fixed package against dated platform rules. They do not execute the Skill or verify task behavior.
.claude/skills/ux-feedback-analyzerRuntime, accounts, dependencies, permissions, network behavior and task quality remain untested.
.agents/skills/ux-feedback-analyzerRuntime, accounts, dependencies, permissions, network behavior and task quality remain untested.
skills/ux-feedback-analyzerRuntime, accounts, dependencies, permissions, network behavior and task quality remain untested.
This command is recorded from the source ecosystem and resolves the registry's latest release. The fixed release shown on this page should be inspected before adoption.
clawhub install @20232931028/ux-feedback-analyzerclawhub inspect @20232931028/ux-feedback-analyzer --version 1.0.0This automated, non-executing scan is bound to this release hash. It is not a safety certification and may contain false positives or false negatives.
This is registry-supplied evidence for the recorded release, not an independent SkillVetAI scan. Check the canonical source for the full report, scanner versions, scope, and current moderation state.
The catalog stores hashes and an inventory summary for change detection. It does not republish the package contents.
sha256:1365ac50589dc582db6b09ee292265d7b7e2d4faa675a6a059e8f4d26ff60e74skill-card.mdSKILL.mdInitial release of ux-feedback-analyzer. - Provides batch analysis of user comments and survey responses for sentiment polarity and pain point classification. - Outputs structured annotations per feedback: sentiment, score, pain point category, and emotional cues. - Includes summary tables: pain point frequency, sentiment averages, top positive/negative points, and top keywords. - Delivers concise insights with priority recommendations and actionable design improvement directions. - Ensures clear distinction between user facts and analytical inferences; highlights critical safety issues.