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Agent Skill · 研究检索

feedback(feedback 数据库)

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。

feedback 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 66,030。

总安装 269周安装 11GitHub Stars 167下载 86核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

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

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

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。

来源仓库内路径:skills/feedback

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/whawkinsiv/claude-code-skills --skill feedback;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

feedback 怎么安装?

在终端执行 npx skills add https://github.com/whawkinsiv/claude-code-skills --skill feedback。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

feedback 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

feedback 需要什么权限?

权限级别是需要联网。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。

feedback 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

feedback 用的人多吗?

公开数据是累计安装 269 次,近一周安装 11 次,下载 86 次,GitHub 167 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

feedback 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
feedback

feedback 数据库 · 本页

269167需要联网未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

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

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。目前只有一个公开来源,建议同时核对源仓库。

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