Review Analysis
liangdabiao/amazon-sorftime-research-MCP-skill
对亚马逊商品评论进行深度分析，自动识别产品痛点、分析退货原因，生成改进建议和客服回复模板。Invoke when user uses /review-analysis command with a product ASIN.
A comprehensive customer/employee feedback analysis pipeline.
Install Feedback Analyzer
$ npx skills add revfactory/harness-100 --skill feedback-analyzer -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install revfactory/harness-100 feedback-analyzer --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/revfactory/harness-100.git skills-src && mkdir -p .claude/skills && cp -r skills-src/en/93-feedback-analyzer/.claude/skills/feedback-analyzer .claude/skills/feedback-analyzer && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "feedback-analyzer" agent skill from https://github.com/revfactory/harness-100/tree/main/en/93-feedback-analyzer/.claude/skills/feedback-analyzer into .claude/skills/feedback-analyzer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "feedback-analyzer", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/revfactory/harness-100/tree/main/en/93-feedback-analyzer/.claude/skills/feedback-analyzerType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add revfactory/harness-100 --skill feedback-analyzer -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install revfactory/harness-100 feedback-analyzer --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/revfactory/harness-100.git skills-src && mkdir -p .agents/skills && cp -r skills-src/en/93-feedback-analyzer/.claude/skills/feedback-analyzer .agents/skills/feedback-analyzer && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "feedback-analyzer" agent skill from https://github.com/revfactory/harness-100/tree/main/en/93-feedback-analyzer/.claude/skills/feedback-analyzer into .agents/skills/feedback-analyzer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "feedback-analyzer", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add revfactory/harness-100 --skill feedback-analyzer -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install revfactory/harness-100 feedback-analyzer --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/revfactory/harness-100.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/en/93-feedback-analyzer/.claude/skills/feedback-analyzer .cursor/skills/feedback-analyzer && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "feedback-analyzer" agent skill from https://github.com/revfactory/harness-100/tree/main/en/93-feedback-analyzer/.claude/skills/feedback-analyzer into .cursor/skills/feedback-analyzer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "feedback-analyzer", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/revfactory/harness-100.git --path en/93-feedback-analyzer/.claude/skills/feedback-analyzer--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add revfactory/harness-100 --skill feedback-analyzer -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install revfactory/harness-100 feedback-analyzer --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/revfactory/harness-100.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/en/93-feedback-analyzer/.claude/skills/feedback-analyzer .gemini/skills/feedback-analyzer && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "feedback-analyzer" agent skill from https://github.com/revfactory/harness-100/tree/main/en/93-feedback-analyzer/.claude/skills/feedback-analyzer into .gemini/skills/feedback-analyzer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "feedback-analyzer", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install revfactory/harness-100 feedback-analyzerInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add revfactory/harness-100 --skill feedback-analyzer -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/revfactory/harness-100.git skills-src && mkdir -p .github/skills && cp -r skills-src/en/93-feedback-analyzer/.claude/skills/feedback-analyzer .github/skills/feedback-analyzer && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "feedback-analyzer" agent skill from https://github.com/revfactory/harness-100/tree/main/en/93-feedback-analyzer/.claude/skills/feedback-analyzer into .github/skills/feedback-analyzer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "feedback-analyzer", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add revfactory/harness-100 --skill feedback-analyzer -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install revfactory/harness-100 feedback-analyzer --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/revfactory/harness-100.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/en/93-feedback-analyzer/.claude/skills/feedback-analyzer .opencode/skills/feedback-analyzer && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "feedback-analyzer" agent skill from https://github.com/revfactory/harness-100/tree/main/en/93-feedback-analyzer/.claude/skills/feedback-analyzer into .opencode/skills/feedback-analyzer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "feedback-analyzer", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
feedback-analyzer- GitHub stars
- 1.3k
- Token cost
- ~1.8k tokens
- SKILL.md length
- 688 words
- Files
- 1
- Skills in repo
- 464
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
A comprehensive customer/employee feedback analysis pipeline.
- Works in 3 steps: Preparation (performed directly by the… → Team Assembly and Execution → Integration and Final Deliverables
- Analyze feedback
- SKILL.md covers Execution Mode, Agent Roster, Workflow and Execution Modes by Scope, plus 4 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Feedback Analyzer is an agent skill from revfactory/harness-100. A comprehensive customer/employee feedback analysis pipeline. An agent team collaborates to handle data collection, sentiment analysis, topic classification, trend detection, and insight reporting. Use this skill for 'analyze feedback', 'customer review analysis', 'survey results analysis', 'VOC analysis', 'employee satisfaction analysis', 'NPS analysis', 'customer complaint analysis', 'feedback trends', 'sentiment analysis', and similar feedback/review/survey analysis topics. Survey design, customer response…
Its SKILL.md is about 1.8k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Sales & Support, covering Customer feedback analysis. The licence is Apache-2.0.
When your agent uses it
- Analyze feedback
- Customer review analysis
- Survey results analysis
- Employee satisfaction analysis
Example prompts
- “analyze feedback”
- “customer review analysis”
- “survey results analysis”
- “/feedback-analyzer”
Workflow steps
3 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit 8e8d35c. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Feedback Analyzer loads about 1.8k tokens when it runs. Until then it costs about 149 tokens; SKILL.md has 688 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from revfactory/harness-100 at commit 8e8d35c, republished under its Apache-2.0 licence (© revfactory). 688 words, ~1,820 tokens.
Download SKILL.mdSave it as
.claude/skills/feedback-analyzer/SKILL.md (or your agent's skills folder).- name
- feedback-analyzer
- description
- A comprehensive customer/employee feedback analysis pipeline. An agent team collaborates to handle data collection, sentiment analysis, topic classification, trend detection, and insight reporting. Use this skill for 'analyze feedback', 'customer review analysis', 'survey results analysis', 'VOC analysis', 'employee satisfaction analysis', 'NPS analysis', 'customer complaint analysis', 'feedback trends', 'sentiment analysis', and similar feedback/review/survey analysis topics. Survey design, customer response manual creation, and CRM system development are out of scope.
Feedback Analyzer — Comprehensive Feedback Analysis Pipeline
Collects and analyzes customer/employee feedback data to produce sentiment analysis, topic classification, trend detection, and insight reports through agent team collaboration.
Execution Mode
Agent Team — 5 members communicate directly via SendMessage and cross-validate each other's work.
Agent Roster
| Agent | File | Role | Type |
|---|---|---|---|
| data-collector | .claude/agents/data-collector.md | Data collection, cleansing, normalization | general-purpose |
| sentiment-analyst | .claude/agents/sentiment-analyst.md | Sentiment analysis, emotion scoring | general-purpose |
| topic-classifier | .claude/agents/topic-classifier.md | Topic classification, category design | general-purpose |
| trend-detector | .claude/agents/trend-detector.md | Trend analysis, anomaly detection | general-purpose |
| insight-writer | .claude/agents/insight-writer.md | Insight report, action items | general-purpose |
Workflow
Phase 1: Preparation (performed directly by the orchestrator)
- Extract from user input:
- Feedback data: Text files, CSV, paste, or verbal description
- Data source type: Customer reviews/surveys/support logs/employee feedback/social media
- Analysis purpose: Product improvement/service quality/employee satisfaction/competitive analysis
- Comparison baseline (optional): Previous period, competitors, targets
- Existing categories (optional): User-defined classification system
- Create the
_workspace/directory in the project root - Organize the input and save to
_workspace/00_input.md - Determine the execution mode based on the request scope
Phase 2: Team Assembly and Execution
| Order | Task | Owner | Dependencies | Deliverable |
|---|---|---|---|---|
| 1 | Data collection/cleansing | collector | None | _workspace/01_data_collection.md |
| 2a | Sentiment analysis | sentiment | Task 1 | _workspace/02_sentiment_analysis.md |
| 2b | Topic classification | classifier | Task 1 | _workspace/03_topic_classification.md |
| 3 | Trend analysis | trend | Tasks 2a, 2b | _workspace/04_trend_report.md |
| 4 | Insight report | writer | Tasks 2a, 2b, 3 | _workspace/05_insight_report.md |
Tasks 2a (sentiment) and 2b (topic) run in parallel. Both depend only on Task 1.
Inter-team communication flow:
- collector completes → sends cleansed data to sentiment, dataset/keywords to classifier, distribution data to trend
- sentiment completes → sends emotion-tagged data to classifier (for cross-analysis), time-series emotion data to trend
- classifier completes → sends topic time-series to trend, categories/urgent issues to writer
- trend completes → sends key trends/anomalies/forecasts to writer
- writer synthesizes all agent results into the insight report
Phase 3: Integration and Final Deliverables
- Verify all files in
_workspace/ - Cross-validation:
- Sentiment analysis count matches data collection count
- Topic classification unclassified rate is 10% or below
- Insights cite data evidence
- Action items follow SMART principles
- Request corrections from the relevant agent if discrepancies are found (up to 2 rounds)
- Report the final summary to the user
Execution Modes by Scope
| User Request Pattern | Execution Mode | Agents Involved |
|---|---|---|
| "Analyze all feedback" | Full Pipeline | All 5 |
| "Just do sentiment analysis" | Sentiment Mode | collector + sentiment |
| "Classify this data by topic" | Classification Mode | collector + classifier |
| "Just look at trends" (existing analysis) | Trend Mode | trend + writer |
| "Just write the executive report" (existing analysis) | Report Mode | writer solo |
Leveraging existing analysis: When the user provides previous analysis results, copy to _workspace/ and skip the corresponding agent.
Show full SKILL.md (271 more words)Show less
Data Transfer Protocol
| Strategy | Method | Usage |
|---|---|---|
| File-based | _workspace/ directory | Primary deliverable storage and sharing |
| Message-based | SendMessage | Real-time key information transfer, correction requests |
| Task-based | TaskCreate/TaskUpdate | Progress tracking, dependency management |
Error Handling
| Error Type | Strategy |
|---|---|
| Data parsing failure | collector processes text-extractable portions only, notes failure sections |
| Extremely small data (fewer than 5) | Include "insufficient for statistical significance" warning, switch to qualitative analysis |
| Mixed languages | Separate analysis by language, analyze primary language only if cross-comparison is not possible |
| High sentiment analysis uncertainty | Tag with "[Confidence: Low]", recommend manual review |
| Agent failure | 1 retry → proceed without that deliverable if still failing, note omission in report |
Test Scenarios
Normal Flow
Prompt: "Analyze this customer review data. It's 200 app store reviews from the last 3 months." Expected Results:
- Data collection: 200 entries cleansed, basic statistics, channel distribution
- Sentiment: Positive/negative/neutral ratios, NPS estimate, extreme sentiment highlights
- Topic: 3-5 major categories, topic × sentiment cross-analysis
- Trends: 3-month sentiment trajectory, anomaly detection
- Insights: Executive Summary, Top 3 insights, priority matrix
Existing File Flow
Prompt: "I have a previous sentiment analysis. Based on that, just create trends and a report." Expected Results:
- Existing sentiment results copied to
_workspace/02_sentiment_analysis.md - Trend mode: trend + writer only
- Trend analysis and insight report generated from existing data
Error Flow
Prompt: "Analyze just 5 customer feedback entries" Expected Results:
- Include "insufficient for statistical significance" warning
- Switch to qualitative analysis: in-depth analysis of individual feedback
- Provide "snapshot analysis" instead of trend analysis
- Report specifies "Additional data collection recommended"
Agent Extension Skills
| Extension Skill | Path | Target Agent | Role |
|---|---|---|---|
| sentiment-scoring | .claude/skills/sentiment-scoring/skill.md | sentiment-analyst | Sentiment classification, scoring, NPS, context correction |
| text-analytics-methods | .claude/skills/text-analytics-methods/skill.md | topic-classifier, trend-detector | Topic classification, keyword analysis, trend detection, insight derivation |
© revfactory, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in en/93-feedback-analyzer/.claude/skills/feedback-analyzer of revfactory/harness-100.
Open the folder on GitHubat commit 8e8d35c
Compare with similar skills
Feedback Analyzer next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Feedback Analyzer this skillrevfactory/harness-100 | 1.3k | — | ~1.8k | Automated safety check: Pass | Apache-2.0 | |
| Review Analysisliangdabiao/amazon-sorftime-research-MCP-skill | 940 | 1 repos | ~2.5k | Automated safety check: Pass | None | |
| Bggg Data Amazonbinggandata/bggg-skills | 603 | — | ~1.4k | Automated safety check: Pass | MIT | |
| Zsxqunnoo/zsxq-skill | 304 | — | ~3.8k | Automated safety check: Pass | MIT | |
| Roadtrip NavigatorWaybox-AI/roadtrip-skill | 126 | — | ~3.4k | Automated safety check: Pass | MIT | |
| Always Compareai-analyst-lab/ai-analyst | 304 | — | ~1.4k | Automated safety check: Pass | MIT |
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Categories
Questions about Feedback Analyzer
What does Feedback Analyzer do?
A comprehensive customer/employee feedback analysis pipeline. Feedback Analyzer is an agent skill from revfactory/harness-100. A comprehensive customer/employee feedback analysis pipeline.
When should I use Feedback Analyzer?
Feedback Analyzer fits situations like: analyze feedback; customer review analysis; survey results analysis; employee satisfaction analysis.
How do I install Feedback Analyzer in Claude Code?
Run `npx skills add revfactory/harness-100 --skill feedback-analyzer -a claude-code`. Or copy the skill folder (en/93-feedback-analyzer/.claude/skills/feedback-analyzer in revfactory/harness-100) into .claude/skills/feedback-analyzer in your project. Claude Code loads it when a task matches its description.
How do I install Feedback Analyzer in Codex?
Run `npx skills add revfactory/harness-100 --skill feedback-analyzer -a codex`. Or copy the skill folder (en/93-feedback-analyzer/.claude/skills/feedback-analyzer in revfactory/harness-100) into .agents/skills/feedback-analyzer in your project. Codex loads it when a task matches its description.
Can I use Feedback Analyzer in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add revfactory/harness-100 --skill feedback-analyzer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/feedback-analyzer, .gemini/skills/feedback-analyzer, .github/skills/feedback-analyzer and .opencode/skills/feedback-analyzer in your project.
What does Feedback Analyzer need to run?
SKILL.md names no scripts, command-line tools or credentials: Feedback Analyzer is instructions for the agent only.
Does Feedback Analyzer access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Feedback Analyzer safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Feedback Analyzer use?
Feedback Analyzer is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Feedback Analyzer use?
About 1.8k tokens (SKILL.md is roughly 7.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Feedback Analyzer?
Skills that share tags, products or a category with Feedback Analyzer: Review Analysis (liangdabiao/amazon-sorftime-research-MCP-skill, 940 stars), Bggg Data Amazon (binggandata/bggg-skills, 603 stars), Zsxq (unnoo/zsxq-skill, 304 stars) and Roadtrip Navigator (Waybox-AI/roadtrip-skill, 126 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Feedback Analyzer?
revfactory (a GitHub user) maintains it in revfactory/harness-100, which has 1,290 GitHub stars. The repository holds 464 skills in this directory. The repository was last updated on March 22, 2026.
Source: revfactory/harness-100 on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.