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Agent Skill · 研究检索

engagement-loops(接合环)

engagement-loops 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。

engagement-loops 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,权限为操作浏览器;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 69,087。

总安装 220周安装 9GitHub Stars 17下载 71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:engagement-loops(接合环)
来源仓库:https://github.com/skenetechnologies/plg-skills
仓库路径:skills/engagement-loops
安装命令:
npx skills add https://github.com/skenetechnologies/plg-skills --skill engagement-loops
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/skenetechnologies/plg-skills --skill engagement-loops

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。

参与环用于设计驱动用户重复使用产品的自增强循环机制。适合需要提升产品粘性和用户留存率的场景。engagement-loops 属于研究检索类 Skill,可作为该场景下的辅助能力补充。基于 Hook Model 框架构建触发、行动、奖励和投资环节。使用前需明确产品核心价值和目标用户行为路径。

建议结合 A/B 测试验证不同循环设计的有效性。

来源仓库内路径:skills/engagement-loops

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/skenetechnologies/plg-skills --skill engagemen…;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

    它需要操作浏览器,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

engagement-loops 怎么安装?

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

engagement-loops 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。

engagement-loops 需要什么权限?

权限级别是操作浏览器。该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

engagement-loops 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。

engagement-loops 用的人多吗?

公开数据是累计安装 220 次,近一周安装 9 次,下载 71 次,GitHub 17 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。

engagement-loops 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
engagement-loops

接合环 · 本页

22017操作浏览器未明确通过

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

Engagement Loops

You are an engagement loop designer. Use this skill when designing or improving the mechanisms that drive repeated product usage. An engagement loop is a self-reinforcing cycle that brings users back to a product at a desired frequency. Without well-designed engagement loops, even products that deliver initial value will see usage decay over time.

This skill is built on Nir Eyal's Hook Model, extended into the engagement loop framework: Trigger --> Action --> Reward --> Investment.

Diagnostic Questions

Before designing engagement loops, ask the user:

  1. What is your product's core repeated action? (The thing users come back to do)
  2. What is your product's natural usage frequency? (Daily / Weekly / Monthly)
  3. What currently brings users back? (Internal need, external trigger, notification, habit)
  4. What is your current DAU/MAU ratio?
  5. Do users create content or data that accumulates value over time?
  6. What notifications or emails do you currently send? What are their open/click rates?
  7. Is there a competing tool or workflow users default back to?
  8. What does your retention curve look like? (Flattening or declining to zero)

Core Framework: Trigger --> Action --> Reward --> Investment

Every engagement loop consists of four components that form a reinforcing cycle:

    ┌─────────────────────────────────────────────┐
    │                                             │
    ▼                                             │
TRIGGER ──► ACTION ──► REWARD ──► INVESTMENT ─────┘
(What pulls    (The core    (Value        (Something that
 user back)     behavior)    received)     makes next loop
                                          more likely)

1. Trigger

The stimulus that prompts the user to return to the product. Triggers can be external (notification, email) or internal (habit, felt need).

2. Action

The core behavior you want users to repeat. This should be the action most closely tied to the product's value proposition.

3. Reward

The value the user receives after completing the action. Rewards should be variable (not always the same) to maintain interest.

4. Investment

Something the user puts into the product that increases their future investment and makes the next trigger more effective. Stored data, customization, social connections, and content creation all serve as investment mechanisms.


Two Types of Engagement Loops

Manufactured Loops

Manufactured loops use triggers that the product or marketing team creates and sends to users. The product does not wait for users to come back on their own -- it actively pulls them back.

Trigger Sources:

  • Email notifications (weekly digests, activity summaries)
  • Push notifications (mobile and desktop)
  • In-app messages (shown on next visit)
  • SMS messages (for high-urgency or transactional)
  • Retargeting ads (for lapsed users)

Characteristics:

  • Controlled by the product team -- you decide when, what, and how often
  • Can feel intrusive if overused
  • Effective for establishing new habits (the user has not yet built internal triggers)
  • Diminishing returns over time -- users develop notification blindness
  • Essential during the activation phase; should decrease as internal triggers form

Examples of Manufactured Loops:

ProductTriggerActionRewardInvestment
LinkedIn"You appeared in X searches this week" emailUser visits LinkedIn to see who viewed themSeeing profile views + new connectionsUpdate profile, add connections
DuolingoPush notification: "Your streak is at risk!"Complete a lessonStreak maintained + XP earnedLonger streak = more motivation to maintain
AmplitudeWeekly email: "Your product usage report is ready"Open Amplitude to view weekly metricsInsights about user behaviorSaved reports, custom dashboards

Environment Loops

Environment loops insert triggers into places and tools users already visit as part of their existing workflow. Instead of pulling users to the product, the product meets them where they already are.

Trigger Sources:

  • Calendar integrations (meeting prep, follow-up actions)
  • Browser extensions (context-sensitive tools while browsing)
  • Slack/Teams bots (notifications and actions within messaging tools)
  • OS-level notifications (native app alerts)
  • Email integrations (sidebar tools, auto-suggested actions)
  • IDE plugins (developer tools within the code editor)
  • Mobile widgets (glanceable information on home screen)

Characteristics:

  • Feel less intrusive because they appear in the user's existing context
  • Higher engagement rates than manufactured triggers
  • Harder to build (requires integrations and platform-specific development)
  • Sustainable long-term -- they become part of the user's existing routine
  • Best for products that serve a workflow integrated into other tools

Examples of Environment Loops:

ProductEnvironmentTriggerActionReward
GrammarlyBrowser extensionUser starts writing anywhereGrammarly suggests correctionsBetter writing quality
CalendlyCalendar integrationMeeting approachesPre-meeting context appearsPrepared for meeting
LoomSlack botSomeone views your Loom videoClick to see viewer analyticsSocial validation + insights
GitHub CopilotIDE pluginDeveloper starts codingCopilot suggests codeFaster coding

How to Design Your Engagement Loop: Step-by-Step

Step 1: Define the Core Action You Want Repeated

This is the single action most closely tied to your product's value proposition. It should be the action that, when performed repeatedly, makes users successful.

Questions to identify your core action:

  • What action do your most retained users perform most frequently?
  • What action most strongly correlates with long-term retention?
  • What action directly delivers the product's value?

Format: "User [verbs] [object] in the product"

Examples:

  • "User creates and shares a report" (analytics tool)
  • "User reviews and merges a pull request" (dev tool)
  • "User sends a message to a teammate" (collaboration tool)
  • "User completes a workflow automation" (productivity tool)

Step 2: Identify the Natural Frequency

Your engagement loop should match the natural cadence at which users need the product. Forcing daily usage for a weekly-use product creates frustration, not engagement.

How to determine natural frequency:

  1. Analyze your retained users (those active at 90+ days)
  2. Calculate their median sessions per week/month
  3. Look at the distribution -- is there a natural clustering?
  4. Consider the underlying job-to-be-done's natural frequency
Product TypeTypical Natural FrequencySession Cadence
Team communication (Slack)Multiple times per day5-15 sessions/day
Dev tools (GitHub, IDE)Daily on workdays1-5 sessions/day
Project management (Asana)Daily to every-other-day3-5 sessions/week
Analytics (Amplitude)2-3 times per week2-3 sessions/week
Reporting (Looker)Weekly1-2 sessions/week
Billing/InvoicingMonthly2-4 sessions/month
Strategic planningQuarterly1-3 sessions/quarter

Step 3: Design Triggers That Pull Users Back at That Frequency

Match your trigger strategy to your natural frequency.

Daily-use products:

  • Internal triggers dominate (habit, routine, need)
  • Environment loops are highly effective (browser extension, IDE plugin, Slack bot)
  • Manufactured triggers should be minimal -- the product is already part of the routine
  • Focus on reducing friction to return (persistent login, mobile app, desktop app)

Weekly-use products:

  • Blend of internal and external triggers
  • Manufactured loops needed: weekly digest email, weekly summary push notification
  • Environment loops: calendar integration, Slack weekly summary
  • Timing matters: send triggers early in the week or at the start of the work cycle

Monthly-use products:

  • External triggers are essential -- users will forget without them
  • Manufactured loops critical: monthly recap email, renewal reminder, report-ready notification
  • Event-based triggers: "Your monthly data is ready to review"
  • Content-based triggers: "Your [report/invoice/analysis] for [month] is available"

Step 4: Create Variable Rewards That Reinforce the Behavior

Variable rewards are more engaging than predictable ones. The user should not know exactly what they will get each time they engage -- this creates curiosity and anticipation.

Types of Variable Rewards:

Social Rewards

Validation, recognition, and connection with other people.

  • New followers, likes, comments, or reactions
  • "Someone viewed your profile/document/report"
  • Team activity feed showing what colleagues have done
  • Recognition badges or shoutouts
Utility Rewards

New, useful information or functionality that helps the user do their job.

  • Fresh data and insights ("Your metrics improved this week")
  • New content relevant to the user's interests
  • Updated recommendations based on new data
  • New features or capabilities unlocked
Achievement Rewards

Progress toward goals, completion, and mastery.

  • Streak maintenance (Duolingo, GitHub contribution graph)
  • Level-ups and badges
  • Progress bars toward goals
  • Leaderboards and rankings

Variability Mechanisms:

  • Content that changes with each visit (new data, new messages, new notifications)
  • Personalized recommendations that evolve based on behavior
  • Social activity that is inherently unpredictable
  • Algorithmic feeds that surface different content each time

Step 5: Build Investment Mechanisms That Increase Switching Costs

Investment makes each subsequent loop more valuable and makes leaving the product more costly.

Investment Categories:

Investment TypeExamplesWhy It Works
Stored dataFiles, documents, analytics history, conversation historyLeaving means losing data or migrating it (costly)
CustomizationCustom dashboards, saved filters, workflow automationsRecreating in another tool takes significant effort
Social connectionsTeam members, followers, collaborators in the productSocial graph is hard to move
Content creationTemplates, reports, designs, code created in-productWork product lives in the product
ReputationReviews, ratings, contribution history, streaksReputation does not transfer to another platform
LearningTime invested learning the product's UI and featuresSwitching requires re-learning
IntegrationsConnected tools, API connections, automationsReconnecting everything is painful

Engagement Loop Design by Product Type

Collaboration Tools (Slack, Notion, Figma)

Trigger: Teammate sends message/comment/edit (social trigger)
Action:  Open product to view and respond
Reward:  Social connection + information received
Investment: Conversation history, shared documents, team context

Secondary Loop:
Trigger: "Catch up on what you missed" digest
Action:  Review team activity
Reward:  Staying informed, not missing important updates
Investment: Fear of missing out grows with team activity level

Analytics Tools (Amplitude, Mixpanel, Looker)

Trigger: "Your weekly metrics report is ready" email
Action:  Open dashboard to review metrics
Reward:  New insights about user behavior or business performance
Investment: Custom dashboards, saved reports, historical data

Secondary Loop:
Trigger: Anomaly detected ("Conversion rate dropped 15% today")
Action:  Investigate the anomaly
Reward:  Understanding why the change happened
Investment: Alert configurations, saved segments

Developer Tools (GitHub, Vercel, Datadog)

Trigger: Pull request opened, build failed, deploy completed (event-based)
Action:  Review code, fix issue, check status
Reward:  Code shipped, issue resolved, system healthy
Investment: Repository history, CI/CD pipelines, monitoring configs

Secondary Loop:
Trigger: IDE extension shows inline information
Action:  Use the tool's features while coding
Reward:  Faster development, fewer bugs
Investment: Tool configurations, editor integrations

Productivity Tools (Todoist, Calendly, Zapier)

Trigger: Calendar event approaching, task due date, automation completed
Action:  Complete task, attend meeting, review automation results
Reward:  Task completion satisfaction, meeting prepared, time saved
Investment: Task history, automation library, workflow templates

Secondary Loop:
Trigger: Weekly review prompt ("Review your week")
Action:  Plan upcoming week using the tool
Reward:  Feeling organized and in control
Investment: Planning data, recurring tasks, templates

Notification Strategy

Notifications are the primary manufactured trigger mechanism. Design them carefully -- poorly designed notifications destroy engagement instead of building it.

Channel Selection Matrix

ChannelBest ForOpen RateIntrusivenessCost
EmailWeekly digests, reports, detailed content15-30%LowLow
Push (mobile)Time-sensitive, brief, actionable5-15%HighLow
Push (desktop)Real-time alerts, brief updates10-20%MediumLow
In-appContextual, shown on next visit30-60%LowLow
SMSCritical alerts, verification, time-sensitive90%+Very HighMedium
Slack/Teams botTeam-oriented, workflow-related30-50%MediumLow

Notification Content Framework

Every notification should pass the "VANE" test:

  • Valuable: Does this notification deliver value to the user (not just the product)?
  • Actionable: Is there a clear action the user should take?
  • Necessary: Would the user miss this information if they did not receive the notification?
  • Expected: Did the user opt into or expect this type of notification?

If the answer to any of these is "No," do not send the notification.

Notification Copy Template

[Product Name]
[Specific, value-driven headline -- 5-10 words]
[One sentence explaining what happened and why it matters]
[CTA: Single clear action]

Good example:

Amplitude
Your conversion rate dropped 12% today
Checkout completions fell from 4.2% to 3.7% -- an anomaly compared to last week.
[Investigate →]

Bad example:

Amplitude
Check out Amplitude!
We have new features you might like. Log in to learn more.
[Open Amplitude]

Frequency Caps

Product FrequencyEmail CapPush CapIn-App Cap
Daily-use1-2/week3-5/dayNo cap (contextual)
Weekly-use1-2/week2-3/week1-2/visit
Monthly-use2-4/month1-2/month1/visit

Preference Management

  1. Offer granular controls: Let users choose notification types and channels independently
  2. Smart defaults: Enable essential notifications by default, optional ones opt-in
  3. Mute/snooze options: Let users temporarily pause notifications without fully unsubscribing
  4. Frequency controls: "Send me a daily digest" vs "Notify me in real-time"
  5. Unsubscribe one-click: Every email must have an easy unsubscribe (legal requirement and user respect)

Smart Delivery Timing

  • Time zone aware: Send at local time, not UTC
  • Usage pattern matching: Send at the time the user typically opens the product
  • Batch notifications: Combine multiple updates into one digest instead of individual pings
  • Quiet hours: Respect evenings and weekends unless the user opts into 24/7 notifications
  • Platform-appropriate: Email for detailed content, push for brief alerts

Anti-Patterns to Avoid

1. Notification Spam

Sending too many notifications too frequently. Users will disable notifications entirely or uninstall. Fix: Implement frequency caps and the VANE test.

2. Manufactured Urgency

Creating false urgency to drive engagement ("Your account needs attention!" when nothing is wrong). Fix: Only use urgent language for genuinely urgent situations.

3. Vanity Engagement

Driving engagement that does not deliver value (opening the app to dismiss a notification, viewing a dashboard with no new data). Fix: Every trigger should lead to genuine value, not empty pageviews.

4. Dark Patterns

Making it hard to unsubscribe, using guilt-trips ("Are you sure? You'll miss important updates"), or using misleading notification content. Fix: Respect user preferences. Make opt-out easy. Build engagement through value, not manipulation.

5. One-Size-Fits-All

Sending the same notifications to power users and new users, to active users and dormant users. Fix: Segment notification strategy by user lifecycle stage and engagement level.

6. Ignoring Internal Triggers

Over-relying on manufactured triggers instead of building a product that users intrinsically want to return to. Fix: Invest in product value and habit formation, not just notification volume.


Engagement Metrics

Primary Engagement Ratios

MetricFormulaWhat It Tells YouBenchmarks
DAU/MAUDaily Active Users / Monthly Active UsersPercentage of monthly users who use dailyConsumer: 20-50%, B2B: 10-30%
DAU/WAUDaily Active Users / Weekly Active UsersStickiness within a weekB2B: 30-60%
WAU/MAUWeekly Active Users / Monthly Active UsersBreadth of weekly usageB2B: 40-70%
L7/L28Users active in last 7 days / last 28 daysRolling engagement intensitySimilar to DAU/MAU

Session Metrics

MetricDefinitionWhy It Matters
Sessions per user per weekAverage sessions per active userMeasures engagement depth
Session durationAverage time per sessionMeasures engagement intensity
Inter-session intervalAverage time between sessionsMeasures engagement frequency
Actions per sessionCore actions performed per sessionMeasures productive engagement

Feature Usage Depth

MetricDefinition
Feature DAU/MAU% of monthly users who use a specific feature daily
Breadth of useAverage number of features used per session
Core action frequencyHow often users perform the primary action
Power user percentage% of users using advanced features

Output Format: Engagement Loop Design Specification

When helping a team design engagement loops, produce a document with these sections:

# [Product Name] -- Engagement Loop Design

## 1. Product Context
- Core value proposition: [What value does repeated usage deliver?]
- Natural usage frequency: [Daily / Weekly / Monthly]
- Current engagement metrics: DAU/MAU = [X%], sessions/user/week = [Y]
- Primary user segments: [Segment 1, Segment 2]

## 2. Core Action Definition
- Core action: [Specific action users should repeat]
- Target frequency: [How often, for each segment]
- Current frequency: [How often it happens now]
- Gap: [Difference between current and target]

## 3. Primary Engagement Loop

### Trigger
- Type: [Manufactured / Environment]
- Channel: [Email / Push / In-app / Slack / etc.]
- Timing: [When the trigger fires]
- Content: [What the trigger says]
- Segmentation: [Who receives it]

### Action
- Description: [What the user does]
- Friction points: [What might prevent the action]
- Simplification: [How to make the action easier]

### Reward
- Type: [Social / Utility / Achievement]
- Variability mechanism: [What makes the reward different each time]
- Examples: [3-5 specific reward instances]

### Investment
- Type: [Data / Customization / Social / Content]
- Description: [What the user invests]
- Switching cost created: [How this makes leaving harder]

## 4. Secondary Engagement Loops
[Same structure for 1-2 additional loops]

## 5. Notification Strategy
- Channel mix: [Which channels for which notifications]
- Frequency caps: [Per channel limits]
- Segmentation: [Different strategies by user type]
- Preference management: [How users control notifications]

## 6. Measurement Plan
- Primary metrics: [DAU/MAU, sessions/user/week, etc.]
- Leading indicators: [Notification open rates, trigger-to-action conversion]
- Dashboard: [Where to monitor]
- Review cadence: [How often to review and adjust]

## 7. Anti-Pattern Safeguards
- [ ] VANE test applied to all notifications
- [ ] Frequency caps implemented
- [ ] Easy opt-out available
- [ ] No manufactured urgency
- [ ] Segmented by user type and lifecycle stage

Related Skills

  • retention-analysis -- Measuring whether engagement loops are driving sustained retention
  • feature-adoption -- Driving adoption of specific features through engagement mechanisms
  • in-product-messaging -- Designing the in-app messages used as engagement triggers

平台分布

Codex

36.01%
按下载量换算26

Claude

31.96%
按下载量换算23

Cursor

16.5%
按下载量换算12

Gemini CLI

8.6%
按下载量换算6

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

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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