Agent skill

Improve Retention

by wondelai in wondelai/skills

Diagnose and fix retention problems using behavior design (B=MAP).

MITAuto-check passedProduct & Project Management

Install Improve Retention

skills CLI
$ npx skills add wondelai/skills --skill improve-retention -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install wondelai/skills improve-retention --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/wondelai/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/improve-retention .claude/skills/improve-retention && rm -rf skills-src

Use ~/.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/

Facts

Skill name
improve-retention
GitHub stars
2.4k
Token cost
~3.8k tokens
SKILL.md length
1,814 words
Files
8 (incl. references)
Skills in repo
62
Repo updated
First seen
Licence
MIT

At a glance

Diagnose and fix retention problems using behavior design (B=MAP).

  • Works in 8 steps: Motivation → Ability → Prompt → …
  • The user mentions users sign up but dont stick around
  • SKILL.md covers Core Principle, Scoring, The Three Elements and Tiny Habits Method, plus 6 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Improve Retention is an agent skill from wondelai/skills. Diagnose and fix retention problems using behavior design (B=MAP). Use when the user mentions "users sign up but dont stick around", "activation rate", "onboarding friction", "retention metrics", "why users dont complete", "churn analysis", or "aha moment". Also trigger when analyzing cohort retention curves, designing activation milestones, reducing time-to-value for new users, or investigating why users quit after their first session. Covers the Ability Chain, prompt design, and tiny behaviors that compound…

Its SKILL.md is about 3.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 8 other files, including reference files (for example `references/ability-chain.md`, `references/behavior-model.md` and `references/case-studies.md`).

It sits in Product & Project Management, covering Prompt engineering and Project management. The repository describes itself as: Wondel.ai Agent Skills — Business, Marketing, UX & Coding Frameworks from Bestselling Books. 50 skills + 12 guided journeys for Claude Code, Codex, Cursor & other agentskills.io… The licence is MIT.

When your agent uses it

  • The user mentions users sign up but dont stick around
  • Activation rate
  • Onboarding friction
  • Retention metrics

Example prompts

  • “users sign up but dont stick around”
  • “activation rate”
  • “onboarding friction”
  • “/improve-retention”

Workflow steps

8 steps, taken from the step headings in SKILL.md.

  1. Motivation
  2. Ability
  3. Prompt
  4. Clarify the Aspiration
  5. Explore Behavior Options
  6. Match Behaviors
  7. Start Tiny
  8. Optimize

What it can do on your machine

Read from SKILL.md and the folder at commit c172996. 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

    Links to these hosts (documentation or services it may open):

    • amazon.com

    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

Improve Retention loads about 3.8k tokens when it runs, and up to ~20k if it reads all its reference files. Until then it costs about 159 tokens; SKILL.md has 1,814 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~159
When it runs · the whole SKILL.md, loaded when a task matches
~3.8k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~20k

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 wondelai/skills at commit c172996, republished under its MIT licence (© wondelai). 1,814 words, ~3,758 tokens.

Download SKILL.mdSave it as .claude/skills/improve-retention/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.
name
improve-retention
description
Diagnose and fix retention problems using behavior design (B=MAP). Use when the user mentions "users sign up but dont stick around", "activation rate", "onboarding friction", "retention metrics", "why users dont complete", "churn analysis", or "aha moment". Also trigger when analyzing cohort retention curves, designing activation milestones, reducing time-to-value for new users, or investigating why users quit after their first session. Covers the Ability Chain, prompt design, and tiny behaviors that compound. For habit loops and variable rewards, see hooked-ux. For intrinsic motivation, see drive-motivation.
license
MIT
metadata.author
wondelai
metadata.version
1.4.0

Behavior Design Framework

Framework for designing products that reliably change behavior. Behavior is not about willpower or motivation — it is a design problem with a predictable equation.

Core Principle

The Fogg Behavior Model = B=MAP. Behavior happens when Motivation, Ability, and a Prompt converge at the same moment.

            HIGH ┃
                 ┃   ★ Behavior happens
                 ┃  (above the Action Line)
                 ┃
  Motivation     ┃━━━━━━━━━━━━━━━━━━━━━━━ ← Action Line
                 ┃
                 ┃   ✗ Behavior fails
                 ┃  (below the Action Line)
            LOW  ┃
                 ┗━━━━━━━━━━━━━━━━━━━━━━━━━
                 HARD                    EASY
                        Ability

The Action Line: When motivation and ability are sufficient, a prompt causes the behavior; below the line, no prompt works. High motivation compensates for low ability and vice versa. The reliable strategy is making behaviors easier (move right), not pumping up motivation (move up).

See: references/behavior-model.md when you need the curve mechanics behind this model — the full Action Line math, behavior types (dot/span/path), and a step-by-step failure diagnostic for a behavior that isn't happening.

Scoring

Goal: 10/10. The six Quick Diagnostic rows are the single source of score-movers. Rate each pass/fail, then start at 10 and subtract per failing row: low motivation or below the Action Line (rows 1-2) cost -2 each; prompts, celebration, bottleneck, and scaling (rows 3-6) cost -1.5 each. A design that passes all six scores 10; one that fails every row scores 0. Map to bands: 9-10 = behavior reliably crosses the Action Line at low motivation, prompts are event/anchor-tied, key actions are celebrated; 5-6 = depends on a motivation spike or optimizes a non-bottleneck factor; <=3 = core action below the Action Line, prompts are spam, no habit wiring. Always state the score and name the specific failing rows.

The Three Elements

1. Motivation

Core concept: Motivation is the energy for action, driven by three core motivators, each with two sides: Sensation (pleasure/pain), Anticipation (hope/fear), Belonging (acceptance/rejection). It is powerful but unreliable.

Why it works: Motivation comes in waves — it spikes (New Year's resolutions, product launches) and crashes (day 3, week 2). Products that depend on high motivation fail when the wave recedes; the best designs work at the trough.

Key insights:

  • "Motivation is unreliable. Ability is not." — BJ Fogg
  • Design for low-motivation moments, not peak excitement
  • Motivation-first tactics (inspiring videos, aspirational messaging) produce spikes, not sustained behavior
  • Match required motivation to behavior difficulty — hard behaviors need high motivation

Product applications:

ContextApplicationExample
OnboardingDon't count on the new-user spike lastingFirst actions work even when excitement fades
Re-engagementAssume returning users have low motivationShow immediate value before asking for effort
MessagingTap the right motivatorSocial fitness → belonging; financial tool → hope

Copy patterns:

  • "Takes 30 seconds" (signals ease, lowers motivation needed)
  • "Join 50,000 teams who..." (belonging motivator)
  • "Don't lose your 7-day streak" (anticipation/fear motivator)

Ethical boundary: A fear motivator (the streak pattern above) is fair only when the loss is real and user-owned (their data, their progress); never invent a loss that exists solely to drive a session.

See: references/motivation-waves.md for the three motivators, motivation waves, and designing for troughs.

2. Ability

Core concept: Ability is the capacity to do the behavior — a function of the scarcest resource across six factors (the Ability Chain). If any single link is too weak, the behavior breaks.

Why it works: Unlike motivation, ability can be systematically engineered: every removed field, eliminated step, and preset default moves the behavior right on the model, crossing the Action Line even at low motivation. The Ability Chain gives you the diagnostic — find the weakest link and fix it.

Key insights:

  • Six factors: Time, Money, Physical Effort, Mental Effort, Social Deviance, Non-Routine
  • Simplicity is a function of the scarcest resource — find the bottleneck, not the most obvious factor
  • "Simplicity changes behavior" — BJ Fogg
  • Starter Steps: shrink the behavior to the tiniest version (2 minutes → 30 seconds → one field)
  • Defaults are the most powerful ability tool — users rarely change them

Product applications:

ContextApplicationExample
SignupCut cost across all six factorsOne-click SSO removes time, mental effort, non-routine
Core actionFix the weakest linkMental-effort bottleneck → smart defaults and templates
Enterprise adoptionAddress social deviance"Your team already uses this" reduces social risk

Copy patterns:

  • "One click to get started" (time + physical effort)
  • "No technical skills needed" (mental effort)
  • "Works just like tools you already use" (non-routine)

Ethical boundary: Reduce friction only on genuinely valuable behaviors — never make it too easy to overspend, over-share, or delete important data without confirmation.

See: references/ability-chain.md for the six factors in detail, friction audit templates, and simplification strategies.

3. Prompt

Core concept: The prompt says "do it now." Without one, behavior doesn't happen regardless of motivation and ability. Three types: Person Prompts (internal reminders), Context Prompts (environmental cues), Action Prompts (designed triggers from the product).

Why it works: Teams assume motivation + ability is enough — it isn't, not without a well-timed prompt. But prompts only work above the Action Line: a push notification to someone lacking motivation or ability is spam.

Key insights:

  • A prompt at the wrong moment is noise; at the right moment, magic
  • Anchor moments tie new behaviors to existing routines ("After I open Slack, I will...")
  • Prompt fatigue is real — every unnecessary prompt degrades the value of future ones

Product applications:

ContextApplicationExample
NotificationsPrompt only above the Action LineSend digest when there's content to review, not on a schedule
Re-engagementTie prompts to real events"Your report is ready" (event-based, not time-based)
Feature discoveryPrompt when motivation and ability alignFeature tour appears when user hits the problem it solves

Copy patterns:

  • "Your weekly report is ready" (context prompt — real event)
  • "One thing left to complete your setup" (action prompt with progress)
  • Never: "We miss you!" (product need, not user need)

Ethical boundary: Every prompt must pass the test "Would I appreciate receiving this right now?" — if it serves a product metric (DAU, re-engagement) but not the user's current goal, cut it.

See: references/prompt-design.md for prompt types, timing strategies, notification design, and anchor moments.

Tiny Habits Method

The practical application of B=MAP: make behaviors so small they need almost no motivation, anchor them to existing routines, and celebrate immediately.

The Recipe
After I [ANCHOR MOMENT], I will [TINY BEHAVIOR], then I [CELEBRATION].
  • Anchor Moment: an existing routine that reliably happens (opening an app, finishing a meeting, morning coffee).
  • Tiny Behavior: the smallest version of the target behavior — not "write a report" but "open the report template."
  • Celebration: an immediate positive emotion that wires the habit. Repetition alone isn't enough — you need the feeling of success.
Starter Steps

Every target behavior has a Starter Step — the tiniest meaningful version:

Target BehaviorStarter StepWhy It Works
Complete onboardingFill in one fieldMomentum from completion
Use analytics dailyOpen the dashboardSeeing data creates curiosity
Collaborate with teamSend one commentSocial reciprocity kicks in
Show full SKILL.md (735 more words)Show less
Scaling Behaviors

Once wired, tiny behaviors grow naturally: open dashboard → check a few metrics → customize → automatic morning habit. Never force scaling — let motivation and momentum drive expansion. The tiny version is the foundation, not a failure.

See: references/tiny-habits.md for the full Tiny Habits recipe, celebration techniques, and scaling patterns.

Behavior Design Process

Fogg's systematic process for lasting behavior change:

Step 1: Clarify the Aspiration

What outcome does the user want — their aspiration, not the product's goal ("stay on top of my team's progress", not "increase DAU").

Step 2: Explore Behavior Options

List all possible behaviors that could achieve the aspiration. Be exhaustive — don't commit yet.

Step 3: Match Behaviors

Assess each for motivation and ease; plot on a 2×2 of impact vs. feasibility (Focus Mapping).

Step 4: Start Tiny

Shrink the best-matched behavior to its Starter Step; design the prompt; add celebration.

Step 5: Optimize

Expand once wired. Fix bottlenecks with the Ability Chain; refine prompt timing from data.

See: references/product-applications.md when applying this process to a specific category — B=MAP mapped to SaaS onboarding, mobile, e-commerce, health, and education with per-category motivation timelines and bottlenecks.

The Action Line

Moving Behaviors Above the Action Line
  • Increase Ability (move right) — remove steps, pre-fill, defaults, templates, wizards. The most reliable approach.
  • Find better Prompts — anchor to existing routines; event-based beats time-based; trigger when motivation is naturally higher.
  • Increasing Motivation (move up) is unreliable — if you need motivation tactics, the behavior is probably too hard.
Retention Diagnostics with B=MAP

Map B=MAP to product metrics:

MetricB=MAP DiagnosisAction
Low activationFirst action below the Action LineShrink onboarding to Starter Step; fix weakest Ability Chain link
Day-1 drop-offPrompt failed or mistimedRedesign first-day prompts; anchor to an existing routine
Day-7 drop-offMotivation wave receded, behavior too hardReduce core action difficulty
Day-30 drop-offHabit didn't form, no internal promptCreate tiny habit recipe; add celebration loops
Low feature adoptionFeature below the Action Line for most usersFriction-audit it; prompt only when motivation is present
Notification fatiguePrompts sent below the Action LineCut volume; send only with motivation + ability

See: references/case-studies.md for a worked diagnosis of Instagram, Duolingo, Slack, Calm, and Peloton — read it to see how M, A, and P are scored independently on a real product before diagnosing your own.

Common Mistakes

MistakeWhy It FailsFix
Relying on motivation for retentionMotivation always recedes; products needing it fail at the troughMake behaviors tiny enough to survive motivation dips
Ignoring the Ability Chain bottleneckYou optimized time but the barrier is mental effort or social devianceAudit all six factors; fix the scarcest resource
Prompting below the Action LineNotifications to unmotivated/unable users = spamEvent-based triggers only when motivation + ability suffice
Skipping celebration in onboardingWithout positive emotion, repetition doesn't wire habitsAdd success states and micro-celebrations after key actions
First action too ambitious"Complete your profile" is a project, not a behaviorShrink to Starter Step: one field, one action
Copying products without diagnosing B=MAPA high-motivation audience's design fails yoursDiagnose your users' motivation, ability, and prompt context first

Quick Diagnostic

QuestionIf NoAction
Can a new user do the core action in under 60 seconds?Ability too lowFriction audit; shrink to Starter Step
Does the product work when motivation is low?Design depends on spikesRedesign core behaviors for minimal motivation
Are prompts tied to real events or anchors?Prompts feel like spamSwitch to event-based or anchor-based prompts
Is there immediate feedback after key actions?No celebration = no habit wiringAdd success states, progress, social feedback
Have you found the weakest Ability Chain link?Optimizing the wrong thingRate each of the six factors 1-5 for the core behavior
Do users scale naturally from tiny behaviors?Forcing complexity too earlyStarter Steps; let behaviors grow organically

Further Reading

Based on BJ Fogg's behavior design research:

About the Author

BJ Fogg, PhD founded the Behavior Design Lab at Stanford University, where he has researched behavior change since 1998. He created the Fogg Behavior Model (B=MAP), coined the term "behavior design", and trained thousands of innovators — including Instagram co-founder Mike Krieger. Tiny Habits distills two decades of that research: lasting change comes from behaviors that are tiny, anchored, and celebrated.

© wondelai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 7 other files (references) in improve-retention of wondelai/skills.

  • SKILL.md
  • references/ability-chain.md
  • references/behavior-model.md
  • references/case-studies.md
  • references/motivation-waves.md
  • references/product-applications.md
  • references/prompt-design.md
  • references/tiny-habits.md

Open the folder on GitHubat commit c172996

Compare with similar skills

Improve Retention 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.

Improve Retention compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Improve Retention this skillwondelai/skills2.4k—~3.8kAutomated safety check: PassMIT
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Hivemind Goalsactiveloopai/hivemind1.6k—~814Automated safety check: PassApache-2.0
Hivemind Goalsactiveloopai/hivemind1.6k—~805Automated safety check: PassApache-2.0
Project Opsericrisco/rsc-harness180—~2.4kAutomated safety check: PassMIT
CCPM Project Managementautomazeio/ccpm8.4k—~1.1kAutomated safety check: PassMIT

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Questions about Improve Retention

What does Improve Retention do?

Diagnose and fix retention problems using behavior design (B=MAP). Improve Retention is an agent skill from wondelai/skills. Diagnose and fix retention problems using behavior design (B=MAP).

When should I use Improve Retention?

Improve Retention fits situations like: the user mentions users sign up but dont stick around; activation rate; onboarding friction; retention metrics.

How do I install Improve Retention in Claude Code?

Run `npx skills add wondelai/skills --skill improve-retention -a claude-code`. Or copy the skill folder (improve-retention in wondelai/skills) into .claude/skills/improve-retention in your project. Claude Code loads it when a task matches its description.

How do I install Improve Retention in Codex?

Run `npx skills add wondelai/skills --skill improve-retention -a codex`. Or copy the skill folder (improve-retention in wondelai/skills) into .agents/skills/improve-retention in your project. Codex loads it when a task matches its description.

Can I use Improve Retention 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 wondelai/skills --skill improve-retention -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/improve-retention, .gemini/skills/improve-retention, .github/skills/improve-retention and .opencode/skills/improve-retention in your project.

What does Improve Retention need to run?

SKILL.md names no scripts, command-line tools or credentials: Improve Retention is instructions for the agent only.

Does Improve Retention access the network?

SKILL.md names 1 domain. As links in the text: amazon.com. This is read from the text; nothing was executed.

Is Improve Retention 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 Improve Retention use?

Improve Retention is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Improve Retention use?

About 3.8k tokens (SKILL.md is roughly 15k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 16k tokens, read only when the agent opens those files.

What are the alternatives to Improve Retention?

Skills that share tags, products or a category with Improve Retention: Hivemind Goals (activeloopai/hivemind, 1.6k stars), Hivemind Goals (activeloopai/hivemind, 1.6k stars), Hivemind Goals (activeloopai/hivemind, 1.6k stars) and Project Ops (ericrisco/rsc-harness, 180 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Improve Retention?

wondelai (a GitHub organization) maintains it in wondelai/skills, which has 2,371 GitHub stars. The repository holds 62 skills in this directory. The repository was last updated on September 10, 2026.

Source: wondelai/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.