Customer Feedback Triage
borghei/Claude-Skills
Inbound customer-feedback triage system. An agent skill from borghei/Claude-Skills.
Synthesize user feedback from multiple channels and identify patterns to inform product decisions.
$ npx skills add nicepkg/ai-workflow --skill customer-feedback-analyzer -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install nicepkg/ai-workflow customer-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/nicepkg/ai-workflow.git skills-src && mkdir -p .claude/skills && cp -r skills-src/workflows/product-manager-workflow/.claude/skills/customer-feedback-analyzer .claude/skills/customer-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 "customer-feedback-analyzer" agent skill from https://github.com/nicepkg/ai-workflow/tree/main/workflows/product-manager-workflow/.claude/skills/customer-feedback-analyzer into .claude/skills/customer-feedback-analyzer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "customer-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/nicepkg/ai-workflow/tree/main/workflows/product-manager-workflow/.claude/skills/customer-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 nicepkg/ai-workflow --skill customer-feedback-analyzer -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install nicepkg/ai-workflow customer-feedback-analyzer --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/nicepkg/ai-workflow.git skills-src && mkdir -p .agents/skills && cp -r skills-src/workflows/product-manager-workflow/.claude/skills/customer-feedback-analyzer .agents/skills/customer-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 "customer-feedback-analyzer" agent skill from https://github.com/nicepkg/ai-workflow/tree/main/workflows/product-manager-workflow/.claude/skills/customer-feedback-analyzer into .agents/skills/customer-feedback-analyzer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "customer-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 nicepkg/ai-workflow --skill customer-feedback-analyzer -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install nicepkg/ai-workflow customer-feedback-analyzer --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/nicepkg/ai-workflow.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/workflows/product-manager-workflow/.claude/skills/customer-feedback-analyzer .cursor/skills/customer-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 "customer-feedback-analyzer" agent skill from https://github.com/nicepkg/ai-workflow/tree/main/workflows/product-manager-workflow/.claude/skills/customer-feedback-analyzer into .cursor/skills/customer-feedback-analyzer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "customer-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/nicepkg/ai-workflow.git --path workflows/product-manager-workflow/.claude/skills/customer-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 nicepkg/ai-workflow --skill customer-feedback-analyzer -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install nicepkg/ai-workflow customer-feedback-analyzer --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/nicepkg/ai-workflow.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/workflows/product-manager-workflow/.claude/skills/customer-feedback-analyzer .gemini/skills/customer-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 "customer-feedback-analyzer" agent skill from https://github.com/nicepkg/ai-workflow/tree/main/workflows/product-manager-workflow/.claude/skills/customer-feedback-analyzer into .gemini/skills/customer-feedback-analyzer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "customer-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 nicepkg/ai-workflow customer-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 nicepkg/ai-workflow --skill customer-feedback-analyzer -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/nicepkg/ai-workflow.git skills-src && mkdir -p .github/skills && cp -r skills-src/workflows/product-manager-workflow/.claude/skills/customer-feedback-analyzer .github/skills/customer-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 "customer-feedback-analyzer" agent skill from https://github.com/nicepkg/ai-workflow/tree/main/workflows/product-manager-workflow/.claude/skills/customer-feedback-analyzer into .github/skills/customer-feedback-analyzer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "customer-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 nicepkg/ai-workflow --skill customer-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 nicepkg/ai-workflow customer-feedback-analyzer --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/nicepkg/ai-workflow.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/workflows/product-manager-workflow/.claude/skills/customer-feedback-analyzer .opencode/skills/customer-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 "customer-feedback-analyzer" agent skill from https://github.com/nicepkg/ai-workflow/tree/main/workflows/product-manager-workflow/.claude/skills/customer-feedback-analyzer into .opencode/skills/customer-feedback-analyzer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "customer-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.
customer-feedback-analyzerSynthesize user feedback from multiple channels and identify patterns to inform product decisions.
Customer Feedback Analyzer is an agent skill from nicepkg/ai-workflow. Synthesize user feedback from multiple channels and identify patterns to inform product decisions. Use when analyzing feedback, prioritizing feature requests, conducting NPS surveys, or understanding user sentiment. Covers feedback collection, categorization, prioritization frameworks, and closing the feedback loop.
Its SKILL.md is about 2.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `manifest.yaml`).
It sits in Sales & Support, covering Customer feedback analysis and Prioritization frameworks. The repository describes itself as: 🚀 170+ pre-built skills for Claude Code, Cursor, Codex & 14+ AI tools. Stop re-teaching your AI the same things. One command → instant domain expertise. Marketing, SEO, Trading… The licence is MIT.
10 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit d167b41. It shows what the files ask for, not the result of running them.
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.
No scripts in the folder and no shell commands in SKILL.md (its code samples are yaml, markdown and javascript).
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Customer Feedback Analyzer loads about 2.5k tokens when it runs. Until then it costs about 86 tokens; SKILL.md has 281 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.
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.
The full file from nicepkg/ai-workflow at commit d167b41, republished under its MIT licence (© nicepkg). 281 words, ~2,476 tokens.
.claude/skills/customer-feedback-analyzer/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.Collect, analyze, and prioritize user feedback to inform product decisions.
Never collect feedback you won't act on. Collecting feedback creates expectation of action. If you can't commit to reviewing and acting on it, don't ask for it. Destroys trust.
Best for: Contextual feedback, low friction
// Contextual feedback
<FeedbackWidget
context={{
page: 'dashboard',
feature: 'export',
user_action: 'clicked_export'
}}
placeholder="How can we improve exports?"
/>Pros: High quality (contextual), immediate Cons: Can interrupt user flow
Best for: Measuring overall satisfaction and loyalty
Question: "How likely are you to recommend [Product] to a friend or colleague?"
Scale: 0-10
Scoring:
Promoters (9-10): Love your product, will advocate
Passives (7-8): Satisfied but not enthusiastic
Detractors (0-6): Unhappy, will churn
NPS = % Promoters - % Detractors
Benchmarks:
Excellent: ≥50
Good: 30-49
Needs Work: <30Follow-up question: "What's the main reason for your score?"
Best for: Identifying recurring issues
Pattern Recognition:
- Same issue reported 5+ times → UX problem, not edge case
- Support time > 10 min per ticket → Needs better docs
- Ticket volume spike → Recent deploy likely caused issueBest for: Deep qualitative insights
Interview Structure:
1. Background (5 min): Their role, use case
2. Problem Discovery (10 min): Challenges they face
3. Solution Validation (10 min): Show prototype, get reaction
4. Wrap-up (5 min): Any other feedback?
Sample Size: 5-10 users per personaBest for: Prioritizing roadmap
Tools: Canny, ProductBoard, Upvoty
Benefits:
- See most requested features
- Reduce duplicate requests
- Public roadmap transparency
- Close the loop automatically
Avoid:
- Building everything requested
- Letting voters drive strategyBest for: Understanding why users churn
Key Questions:
- What made you decide to cancel?
- What feature/change would have kept you?
- What are you switching to?
- What did we do well?Bug: Something broken
- "Export fails with >100 rows"
- Priority: Fix immediately
Feature Request: New capability
- "Add Slack integration"
- Priority: Vote/validate
Enhancement: Improve existing feature
- "Export should include timestamps"
- Priority: Nice to have
Usability: Confusing UX
- "Can't find where to invite team members"
- Priority: High (friction)
Performance: Speed issue
- "Dashboard loads slowly"
- Priority: Depends on impactCritical: Blocks core workflow
- "Can't save projects"
- Action: Hotfix immediately
High: Significant friction
- "Onboarding confusing"
- Action: Fix this sprint
Medium: Minor annoyance
- "Button text unclear"
- Action: Fix next quarter
Low: Edge case or cosmetic
- "Spacing looks off on mobile"
- Action: BacklogWidespread: 50+ reports
→ High priority
Common: 10-50 reports
→ Medium priority
Occasional: 5-10 reports
→ Low priority, monitor
Rare: <5 reports
→ Likely edge case, document workaroundPower Users: High engagement, experienced
→ Actionable, technical feedback
New Users: Recently signed up
→ Onboarding issues, first impressions
Churned Users: Cancelled/inactive
→ Why did they leave?
Enterprise: Paying customers
→ Security, compliance, integrationsScore = Impact (1-5) × Frequency (1-5) × Strategic Alignment (1-5)
Score ≥ 40: High Priority (next sprint)
Score 20-39: Medium Priority (next quarter)
Score < 20: Low Priority (backlog or never)Example:
Feedback: "Add Slack integration"
Impact: 4 (significantly improves collaboration)
Frequency: 5 (50+ requests)
Strategic Alignment: 4 (fits roadmap)
Score: 4 × 5 × 4 = 80
Decision: HIGH PRIORITY - Build next sprint
Feedback: "Change button color"
Impact: 1 (minor cosmetic)
Frequency: 1 (1 person mentioned)
Strategic Alignment: 1 (not strategic)
Score: 1 × 1 × 1 = 1
Decision: LOW PRIORITY - BacklogEmail Template:
Subject: Thanks for your feedback!
Hi [Name],
Thanks for taking the time to share your thoughts on [topic].
We review all feedback and use it to prioritize our roadmap. I've shared
your input with the product team.
You can track feature requests on our public roadmap: [link]
Thanks for helping us improve!
[Your Name]Decision Tree: Is it reported 10+ times?
Yes → Add to roadmap
No → Monitor
Does it align with strategy?
Yes → Prioritize
No → Document why not
Can we ship in 2 weeks?
Yes → Quick win, do it
No → Add to backlogEmail Template:
Subject: You asked for [Feature] - it's live!
Hi [Name],
Remember when you asked us to add [feature]? Good news - it's live!
[Screenshot/GIF of feature]
Here's how it works:
1. [Step 1]
2. [Step 2]
Try it now: [Link]
Thanks for the feedback that made this happen.
[Your Name]
P.S. Have more ideas? Reply to this email.## [Feature] is now live!
Requested by 47 users, [Feature] lets you [benefit].
How it works:
- [Key point 1]
- [Key point 2]
Try it: [Link]
Thanks to everyone who suggested this!Problem: Vocal minority ≠ Real need
Example:
- 1 user emails daily about dark mode
- Analytics show 2% use dark mode
Action: Validate with data before buildingProblem: Users leave without complaining
Example:
- Retention drops from 40% to 30%
- No feedback, no complaints
Action:
- Proactive exit interviews
- Check analytics for drop-off points
- Run usability testsProblem: Building everything requested leads to bloat
Example:
- 'Add Excel export'
- 'Add CSV export'
- 'Add JSON export'
- 'Add PDF export'
Action: Build generic solution, not every variantfeedback_summary:
period: "2024-01-15 to 2024-01-22"
total_items: 87
top_themes:
- theme: "Slack Integration"
frequency: 23
severity: high
example_quotes:
- "We need Slack notifications"
- "Can't notify team without Slack"
recommended_action: "Build Slack integration next sprint"
- theme: "Slow Dashboard Load"
frequency: 15
severity: medium
example_quotes:
- "Dashboard takes 10+ seconds"
- "Performance is terrible"
recommended_action: "Optimize queries, add caching"
- theme: "Mobile App Request"
frequency: 8
severity: low
example_quotes:
- "I want a mobile app"
recommended_action: "Monitor, not enough demand yet"
nps:
score: 42
detractor_reasons:
- "Too expensive" (12 mentions)
- "Missing features" (8 mentions)
- "Slow performance" (5 mentions)
prioritized_backlog:
- feedback: "Add Slack integration"
score: 80
priority: high
- feedback: "Optimize dashboard performance"
score: 45
priority: medium
- feedback: "Mobile app"
score: 16
priority: lowFeedback Collection:
- In-app: Canny, UserVoice, Intercom
- Surveys: Typeform, SurveyMonkey, Delighted (NPS)
- User Research: Calendly, Zoom, UserTesting.com
Analysis:
- Qualitative: Dovetail, Notion, Airtable
- Quantitative: Excel, Google Sheets, Tableau
- Sentiment: MonkeyLearn, Lexalytics
Roadmap Transparency:
- Public Roadmap: Canny, ProductBoard, Trello
- Changelog: Headway, ReleaseNotes.io, BeamerDaily:
- Review support tickets
- Monitor in-app feedback
Weekly:
- Synthesize themes
- Share with product team
- Prioritize top requests
Monthly:
- Send NPS survey
- Review feature requests
- Update public roadmap
Quarterly:
- User interviews (5-10)
- Exit surveys for churned users
- Competitive feedback analysis❌ Collecting feedback without acting: Damages trust ❌ Building everything requested: Feature bloat ❌ Not validating with data: Vocal minority ≠ majority ❌ Ignoring silent majority: Not everyone gives feedback ❌ No follow-up: Users want to know you listened
Great feedback analysis:
© nicepkg, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 1 other file in workflows/product-manager-workflow/.claude/skills/customer-feedback-analyzer of nicepkg/ai-workflow.
Open the folder on GitHubat commit d167b41
Customer 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 |
|---|---|---|---|---|---|---|
| Customer Feedback Analyzer this skillnicepkg/ai-workflow | 285 | — | ~2.5k | Automated safety check: Pass | MIT | |
| Customer Feedback Triageborghei/Claude-Skills | 881 | — | ~2.1k | Automated safety check: Pass | MIT | |
| Review Analysisliangdabiao/amazon-sorftime-research-MCP-skill | 946 | 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 | |
| Siftranknoperator/siftrank | 224 | — | ~2.9k | Automated safety check: Pass | MIT |
borghei/Claude-Skills
Inbound customer-feedback triage system. An agent skill from borghei/Claude-Skills.
liangdabiao/amazon-sorftime-research-MCP-skill
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知识星球 CLI(zsxq-cli)与底层接口完整操作指南,涵盖星球和内容管理、Skill Pay 微信支付场景。当用户提到知识星球、zsxq、小密圈、星球、登录/认证、发帖、评论、回答、编辑、删除主题、定时发布/定时任务/定时回答、投票、问答主题、markdown 正文、AI…
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Categories
Synthesize user feedback from multiple channels and identify patterns to inform product decisions. Customer Feedback Analyzer is an agent skill from nicepkg/ai-workflow. Synthesize user feedback from multiple channels and identify patterns to inform product decisions.
Customer Feedback Analyzer fits situations like: analyzing feedback; prioritizing feature requests; conducting NPS surveys; understanding user sentiment.
Run `npx skills add nicepkg/ai-workflow --skill customer-feedback-analyzer -a claude-code`. Or copy the skill folder (workflows/product-manager-workflow/.claude/skills/customer-feedback-analyzer in nicepkg/ai-workflow) into .claude/skills/customer-feedback-analyzer in your project. Claude Code loads it when a task matches its description.
Run `npx skills add nicepkg/ai-workflow --skill customer-feedback-analyzer -a codex`. Or copy the skill folder (workflows/product-manager-workflow/.claude/skills/customer-feedback-analyzer in nicepkg/ai-workflow) into .agents/skills/customer-feedback-analyzer in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add nicepkg/ai-workflow --skill customer-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/customer-feedback-analyzer, .gemini/skills/customer-feedback-analyzer, .github/skills/customer-feedback-analyzer and .opencode/skills/customer-feedback-analyzer in your project.
SKILL.md names no scripts, command-line tools or credentials: Customer Feedback Analyzer is instructions for the agent only.
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.
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.
Customer Feedback Analyzer is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.5k tokens (SKILL.md is roughly 9.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Customer Feedback Analyzer: Customer Feedback Triage (borghei/Claude-Skills, 881 stars), Review Analysis (liangdabiao/amazon-sorftime-research-MCP-skill, 946 stars), Bggg Data Amazon (binggandata/bggg-skills, 603 stars) and Zsxq (unnoo/zsxq-skill, 304 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
nicepkg (a GitHub organization) maintains it in nicepkg/ai-workflow, which has 285 GitHub stars. The repository holds 61 skills in this directory. The repository was last updated on January 20, 2026.
Source: nicepkg/ai-workflow on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.