Real Skill packageSource verifiedClawHub registry

feedbacklens-analysis

Automatically cluster a batch of user feedback (text/CSV/Excel), rank priorities with a quantitative "frequency × severity × impact scope" algorithm, produce actionable improvement suggestions, and generate a visual report. Built-in industry severity anchors (SaaS/E-commerce/Mobile App/Food Delivery

Identity and source

Publisher attributiondongtottiregistry owner unverified by skillvetai
Functional categoryData, Spreadsheets & Analyticsautomatically inferred · 58% rule confidence
Package forminstruction with code8 recorded files
Canonical sourceClawHub registryclawhub:dongtotti:feedbacklens-analysis
Open canonical source ↗

Platform declarations

These states come from the source or distribution context. None of the entries below are SkillVetAI compatibility test results.

OpenClawnative officialProvenance: registry distribution

Independent structural checks

These checks parse the fixed package against dated platform rules. They do not execute the Skill or verify task behavior.

Claude Codepasses structure
Checker 0.1.0 · agent-skills-2026-08-13+claude-code-docs-2026-08-13 · 9/17/2026.claude/skills/feedbacklens-analysis

Runtime, accounts, dependencies, permissions, network behavior and task quality remain untested.

OpenAI Codexpasses structure
Checker 0.1.0 · agent-skills-2026-08-13+codex-docs-2026-08-13 · 9/17/2026.agents/skills/feedbacklens-analysis

Runtime, accounts, dependencies, permissions, network behavior and task quality remain untested.

OpenClawpasses structure
Checker 0.1.0 · agent-skills-2026-08-13+openclaw-docs-2026-08-13 · 9/17/2026skills/feedbacklens-analysis

Runtime, accounts, dependencies, permissions, network behavior and task quality remain untested.

Installation and inspection

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 @dongtotti/feedbacklens-analysis
clawhub inspect @dongtotti/feedbacklens-analysis --version 1.2.1

Security evidence

SkillVetAI static result: no findings detected

This automated, non-executing scan is bound to this release hash. It is not a safety certification and may contain false positives or false negatives.

Status
completed
Coverage
full text content
Files
7 / 8 inspected as text
Checked
9/17/2026, 4:50:34 AM
Scanner
0.1.3
Policy
1.0.3
2 inferred permission indicators
  • network access — automatically inferred
  • filesystem write — automatically inferred
1 dependency and API indicators
  • api: www.feedbacklens.cn
External clawhub result: clean

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.

Evidence checked
9/17/2026, 1:04:45 AM
Release binding
Matches this record
  • vt: clean
  • skillspector: suspicious
  • llm: clean

Recorded files

The catalog stores hashes and an inventory summary for change detection. It does not republish the package contents.

Package content hashsha256:3c75632147eb6e231a4c68130e5c38139ac4cec0a383cf101bdeaa5e066b08de
Show up to 8 recorded paths
  • demo_evaluation.json
  • demo_feedback.csv
  • icon.png
  • priority_cases.json
  • README.md
  • render_report.py
  • report_template.html
  • SKILL.md

Source changelog

- Added a comprehensive "demo mode": Users can now generate a full sample analysis report using 36 built-in feedback samples immediately after installation, with no data preparation required. - Enhanced documentation with clear description of demo features, industry severity anchors, and analysis steps, including strict scoring and evaluation rubrics. - Improved report outputs: Now ensures evidence citation, reproducible scoring, and actionable, step-based suggestions for each high-priority cluster. - Strict input handling and data cleaning clarified, with assured support for diverse feedback formats (text/CSV/Excel) and sources (app reviews, tickets, surveys, etc.). - Output summary, HTML report generation, and file naming conventions are now strictly standardized, including explicit demo labeling to prevent confusion with real data.