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feedbackfeedback 数据库

Agent Skill

feedback 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

269

周安装

11

GitHub Stars

167

下载量

86
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:feedback(feedback 数据库)
来源仓库:https://github.com/whawkinsiv/claude-code-skills
仓库路径:skills/feedback
安装命令:
npx skills add https://github.com/whawkinsiv/claude-code-skills --skill feedback
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/whawkinsiv/claude-code-skills --skill feedback

简介

feedback 用于查找、检索和筛选相关信息。

  • 适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词快速定位候选结果。
  • 通过 npx skills add 命令从指定仓库安装并使用。
  • 安装前需确认权限范围、维护状态,避免触发联网或命令执行。
  • 建议结合原始 README 核验具体用法和功能边界。

SKILL.md

User Feedback & Feature Requests

Feedback is abundant but insight is rare. Your job is not to build everything users ask for — it's to understand the problems behind the requests. This skill helps you collect, prioritize, and act on feedback without drowning in it.

Core Principles

  • Feedback is a gift, but not all gifts are useful. Filter signal from noise.
  • Users describe solutions. Your job is to find the problem underneath.
  • "Build what customers ask for" is wrong. "Solve the problems customers reveal" is right.
  • A feedback system you actually use beats a perfect one you ignore. Start simple.
  • Closing the loop (telling users what you did with their feedback) is the most powerful retention tool you have.

Feedback Collection Methods

Ranked by Signal Quality

MethodSignal QualityEffortBest For
1-on-1 conversationsHighestHighEarly stage, understanding "why"
Support ticket analysisHighLowFinding recurring pain points
In-app feedback widgetHighLowContextual, in-the-moment feedback
NPS surveyMediumLowTracking sentiment over time
Cancellation surveyHighLowUnderstanding churn drivers
Feature request boardMediumLowAggregating demand signals
Social media mentionsMediumLowUnfiltered opinions
Usage analyticsHighMediumWhat users DO vs. what they SAY

What to Use When

0-50 users:    Talk to every user. Email them. Get on calls. No tools needed.
50-200 users:  In-app feedback widget + cancellation survey + monthly NPS
200-500 users: Add a public feature request board + quarterly user interviews
500+ users:    All of the above + systematic ticket analysis

In-App Feedback

Simple Feedback Widget

Tell AI:

Add a feedback widget to my app. Requirements:
- Small "Feedback" button fixed to the bottom-right corner
- Clicking opens a simple form: text area + optional email
- Includes the current page URL and user ID automatically
- Saves to a [feedback] table in the database
- Shows a "Thank you" message after submission
- No third-party tool needed — just store it in the database

Contextual Feedback Triggers

Collect feedback at the right moment:

TriggerQuestion
After completing a key action"How was that experience? (1-5)"
After 7 days of usage"What's the one thing you'd improve?"
After upgrading"What made you decide to upgrade?"
After using a new feature"Was this feature helpful? Yes / No / Needs improvement"
After a support interaction"Did we resolve your issue? (1-5)"

NPS (Net Promoter Score)

How It Works

Ask one question: "How likely are you to recommend [Product] to a friend? (0-10)"

  • 0-6: Detractors (unhappy, at risk of churning)
  • 7-8: Passives (satisfied but not enthusiastic)
  • 9-10: Promoters (loyal, will refer others)

NPS = % Promoters - % Detractors

NPS Benchmarks for SaaS

ScoreAssessment
< 0More detractors than promoters. Fix the product
0-30Average. Room to improve
30-50Good. Users like your product
50+Excellent. Strong word-of-mouth potential

Running an NPS Survey

Tell AI:

Add a quarterly NPS survey to my app.
- Show to users who have been active for 30+ days
- Question: "How likely are you to recommend [Product]? (0-10)"
- Follow-up: "What's the main reason for your score?" (open text)
- Don't show to users who responded in the last 90 days
- Store responses with user ID and timestamp
- Dashboard showing NPS trend over time

Follow up based on score:

ScoreAction
0-6 (Detractor)Personal email: "I saw your feedback. Can I help?"
7-8 (Passive)Ask: "What would make us a 9 or 10?"
9-10 (Promoter)Ask for a review, testimonial, or referral

Feature Request Management

The Feature Request Board

A public or internal board where requests are collected and prioritized.

Simple options:

  • Canny (free tier available)
  • Fider (open source, self-hosted)
  • Notion board (free, manual)
  • GitHub Discussions (free, developer-friendly)

Tell AI:

Help me set up a feature request system using [Notion / database table].
I need:
- Users can submit requests (title + description)
- Users can upvote existing requests
- I can tag requests by category and status
- Status options: Under Review, Planned, In Progress, Shipped, Won't Do
- A public-facing view and a private admin view

Processing Feature Requests

Not every request deserves action. Use this filter:

For each feature request, ask:
1. How many users requested this? (1 user = anecdote, 10+ = pattern)
2. What's the problem behind the request? (they want X, but WHY?)
3. Does it align with our product direction?
4. How much effort to build? (hours, not weeks)
5. Will it reduce churn, increase conversion, or expand revenue?

Score: Impact (1-5) × Confidence (1-5) / Effort (1-5) = Priority Score

What Users Say vs. What They Mean

What They SayWhat They Might Mean
"Can you add a calendar view?""I need to see my tasks by date" (many solutions)
"I want an API""I want to connect this to my other tools" (Zapier might work)
"Make it faster""The dashboard takes too long to load" (specific page, specific fix)
"Add more customization""The defaults don't fit my workflow" (better defaults might fix it)
"Build a mobile app""I need to check one thing on my phone" (responsive web might work)

Closing the Feedback Loop

The most underused retention tool. When you ship something a user asked for, tell them:

Shipped Notification

Subject: You asked, we built it — [Feature Name] is live

Hi [Name],

A few weeks ago you told us you wanted [what they asked for].
I'm happy to let you know it's live now.

Here's how to use it: [link or quick instructions]

Thanks for shaping the product — your feedback directly drives
what we build next.

[Your name]

Monthly Changelog

Subject: What's new in [Product] — [Month]

Here's what we shipped this month:

Built because you asked:
- [Feature] — requested by [X] users
- [Improvement] — based on your feedback

Bug fixes:
- [Fix 1]
- [Fix 2]

Coming next:
- [Planned feature 1]
- [Planned feature 2]

Have feedback? Reply to this email or use the feedback button in the app.

Feedback Metrics

Track monthly:

| Metric                          | This Month | Last Month |
|---------------------------------|------------|------------|
| Total feedback items received   |            |            |
| NPS score                       |            |            |
| Top 3 requested features        |            |            |
| Features shipped from feedback  |            |            |
| Avg time from request to ship   |            |            |
| Feedback response rate          |            |            |

Common Mistakes

MistakeFix
Building every feature users ask forPrioritize by impact, confidence, and effort
Collecting feedback but never acting on itReview feedback weekly. Ship something from it monthly
Never telling users you shipped their requestClose the loop. Always notify them
Only listening to the loudest usersQuiet users churn silently. Reach out proactively
Treating feature requests as specsUsers describe solutions. Your job is to find the problem
No system — feedback in email, Slack, DMsCentralize all feedback in one place
Asking for feedback too oftenNPS quarterly. In-app widget always available. Don't pester

Success Looks Like

  • Every piece of feedback goes into one centralized system
  • You review feedback weekly and act on it monthly
  • Users know their feedback is heard (closed loop)
  • Your roadmap is informed by feedback data, not gut feelings
  • NPS trending upward quarter over quarter

Related Skills

  • prioritize — Turn feedback into prioritized feature decisions
  • customer-research — Deeper research beyond surface-level feedback
  • retention — Close the feedback loop to reduce churn
  • analytics — Quantify feedback themes with usage data

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

38.89%
按下载量换算33

Claude

30.07%
按下载量换算26

Cursor

19.46%
按下载量换算17

Gemini CLI

9.29%
按下载量换算8

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

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