Hivemind Goals
activeloopai/hivemind
Create, track and update team goals via the Deeplake virtual filesystem at memory/goal/.
Diagnose and fix retention problems using behavior design (B=MAP).
$ npx skills add wondelai/skills --skill improve-retention -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install wondelai/skills improve-retention --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/wondelai/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/improve-retention .claude/skills/improve-retention && 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 "improve-retention" agent skill from https://github.com/wondelai/skills/tree/main/improve-retention into .claude/skills/improve-retention/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "improve-retention", 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/wondelai/skills/tree/main/improve-retentionType 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 wondelai/skills --skill improve-retention -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install wondelai/skills improve-retention --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/wondelai/skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/improve-retention .agents/skills/improve-retention && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "improve-retention" agent skill from https://github.com/wondelai/skills/tree/main/improve-retention into .agents/skills/improve-retention/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "improve-retention", 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 wondelai/skills --skill improve-retention -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install wondelai/skills improve-retention --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/wondelai/skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/improve-retention .cursor/skills/improve-retention && 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 "improve-retention" agent skill from https://github.com/wondelai/skills/tree/main/improve-retention into .cursor/skills/improve-retention/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "improve-retention", 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/wondelai/skills.git --path improve-retention--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 wondelai/skills --skill improve-retention -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install wondelai/skills improve-retention --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/wondelai/skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/improve-retention .gemini/skills/improve-retention && 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 "improve-retention" agent skill from https://github.com/wondelai/skills/tree/main/improve-retention into .gemini/skills/improve-retention/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "improve-retention", 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 wondelai/skills improve-retentionInstalls 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 wondelai/skills --skill improve-retention -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/wondelai/skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/improve-retention .github/skills/improve-retention && 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 "improve-retention" agent skill from https://github.com/wondelai/skills/tree/main/improve-retention into .github/skills/improve-retention/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "improve-retention", 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 wondelai/skills --skill improve-retention -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install wondelai/skills improve-retention --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/wondelai/skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/improve-retention .opencode/skills/improve-retention && 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 "improve-retention" agent skill from https://github.com/wondelai/skills/tree/main/improve-retention into .opencode/skills/improve-retention/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "improve-retention", 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.
improve-retentionDiagnose 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). 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.
8 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit c172996. 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.
From the folder's file list and the shell code blocks in SKILL.md.
Links to these hosts (documentation or services it may open):
amazon.comFrom 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.
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.
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 wondelai/skills at commit c172996, republished under its MIT licence (© wondelai). 1,814 words, ~3,758 tokens.
.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.Framework for designing products that reliably change behavior. Behavior is not about willpower or motivation — it is a design problem with a predictable equation.
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
AbilityThe 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.
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.
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:
Product applications:
| Context | Application | Example |
|---|---|---|
| Onboarding | Don't count on the new-user spike lasting | First actions work even when excitement fades |
| Re-engagement | Assume returning users have low motivation | Show immediate value before asking for effort |
| Messaging | Tap the right motivator | Social fitness → belonging; financial tool → hope |
Copy patterns:
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.
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:
Product applications:
| Context | Application | Example |
|---|---|---|
| Signup | Cut cost across all six factors | One-click SSO removes time, mental effort, non-routine |
| Core action | Fix the weakest link | Mental-effort bottleneck → smart defaults and templates |
| Enterprise adoption | Address social deviance | "Your team already uses this" reduces social risk |
Copy patterns:
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.
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:
Product applications:
| Context | Application | Example |
|---|---|---|
| Notifications | Prompt only above the Action Line | Send digest when there's content to review, not on a schedule |
| Re-engagement | Tie prompts to real events | "Your report is ready" (event-based, not time-based) |
| Feature discovery | Prompt when motivation and ability align | Feature tour appears when user hits the problem it solves |
Copy patterns:
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.
The practical application of B=MAP: make behaviors so small they need almost no motivation, anchor them to existing routines, and celebrate immediately.
After I [ANCHOR MOMENT], I will [TINY BEHAVIOR], then I [CELEBRATION].Every target behavior has a Starter Step — the tiniest meaningful version:
| Target Behavior | Starter Step | Why It Works |
|---|---|---|
| Complete onboarding | Fill in one field | Momentum from completion |
| Use analytics daily | Open the dashboard | Seeing data creates curiosity |
| Collaborate with team | Send one comment | Social reciprocity kicks in |
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.
Fogg's systematic process for lasting behavior change:
What outcome does the user want — their aspiration, not the product's goal ("stay on top of my team's progress", not "increase DAU").
List all possible behaviors that could achieve the aspiration. Be exhaustive — don't commit yet.
Assess each for motivation and ease; plot on a 2×2 of impact vs. feasibility (Focus Mapping).
Shrink the best-matched behavior to its Starter Step; design the prompt; add celebration.
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.
Map B=MAP to product metrics:
| Metric | B=MAP Diagnosis | Action |
|---|---|---|
| Low activation | First action below the Action Line | Shrink onboarding to Starter Step; fix weakest Ability Chain link |
| Day-1 drop-off | Prompt failed or mistimed | Redesign first-day prompts; anchor to an existing routine |
| Day-7 drop-off | Motivation wave receded, behavior too hard | Reduce core action difficulty |
| Day-30 drop-off | Habit didn't form, no internal prompt | Create tiny habit recipe; add celebration loops |
| Low feature adoption | Feature below the Action Line for most users | Friction-audit it; prompt only when motivation is present |
| Notification fatigue | Prompts sent below the Action Line | Cut 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.
| Mistake | Why It Fails | Fix |
|---|---|---|
| Relying on motivation for retention | Motivation always recedes; products needing it fail at the trough | Make behaviors tiny enough to survive motivation dips |
| Ignoring the Ability Chain bottleneck | You optimized time but the barrier is mental effort or social deviance | Audit all six factors; fix the scarcest resource |
| Prompting below the Action Line | Notifications to unmotivated/unable users = spam | Event-based triggers only when motivation + ability suffice |
| Skipping celebration in onboarding | Without positive emotion, repetition doesn't wire habits | Add success states and micro-celebrations after key actions |
| First action too ambitious | "Complete your profile" is a project, not a behavior | Shrink to Starter Step: one field, one action |
| Copying products without diagnosing B=MAP | A high-motivation audience's design fails yours | Diagnose your users' motivation, ability, and prompt context first |
| Question | If No | Action |
|---|---|---|
| Can a new user do the core action in under 60 seconds? | Ability too low | Friction audit; shrink to Starter Step |
| Does the product work when motivation is low? | Design depends on spikes | Redesign core behaviors for minimal motivation |
| Are prompts tied to real events or anchors? | Prompts feel like spam | Switch to event-based or anchor-based prompts |
| Is there immediate feedback after key actions? | No celebration = no habit wiring | Add success states, progress, social feedback |
| Have you found the weakest Ability Chain link? | Optimizing the wrong thing | Rate each of the six factors 1-5 for the core behavior |
| Do users scale naturally from tiny behaviors? | Forcing complexity too early | Starter Steps; let behaviors grow organically |
Based on BJ Fogg's behavior design research:
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
SKILL.md and 7 other files (references) in improve-retention of wondelai/skills.
Open the folder on GitHubat commit c172996
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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Improve Retention this skillwondelai/skills | 2.4k | — | ~3.8k | Automated safety check: Pass | MIT | |
| Hivemind Goalsactiveloopai/hivemind | 1.6k | — | ~1.7k | Automated safety check: Notes | Apache-2.0 | |
| Hivemind Goalsactiveloopai/hivemind | 1.6k | — | ~814 | Automated safety check: Pass | Apache-2.0 | |
| Hivemind Goalsactiveloopai/hivemind | 1.6k | — | ~805 | Automated safety check: Pass | Apache-2.0 | |
| Project Opsericrisco/rsc-harness | 180 | — | ~2.4k | Automated safety check: Pass | MIT | |
| CCPM Project Managementautomazeio/ccpm | 8.4k | — | ~1.1k | Automated safety check: Pass | MIT |
activeloopai/hivemind
Create, track and update team goals via the Deeplake virtual filesystem at memory/goal/.
activeloopai/hivemind
Create, track and update team goals in Hivemind via the hivemind CLI.
activeloopai/hivemind
Create, track, and read team goals via Hivemind from openclaw.
ericrisco/rsc-harness
A skill your agent uses when an operator wants to run a small or mid-sized project from a flat file instead of standing up Jira or Asana — dated milestones each with one named owner and a binary…
automazeio/ccpm
Runs a spec-driven workflow from PRD to epic to GitHub issues to parallel agents, with status, standup and blocked-work reports from bundled scripts.
astral-sh/claude-code-plugins
Guide for using uv, the Python package and project manager. An agent skill from astral-sh/claude-code-plugins.
wondelai/skills
Navigate the technology adoption lifecycle from early adopters to mainstream market.
wondelai/skills
Apply foundational design principles: affordances, signifiers, constraints, feedback, and conceptual models.
wondelai/skills
Run a structured 5-day process to prototype, test, and validate product ideas with real users.
wondelai/skills
Design habit-forming product loops using the Hook Model (Trigger, Action, Variable Reward, Investment).
wondelai/skills
Design products and pricing around validated willingness to pay, from Ramanujam & Tacke's "Monetizing Innovation".
wondelai/skills
Build a scalable outbound B2B sales machine with specialized roles (SDR, AE, CSM).
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).
Improve Retention fits situations like: the user mentions users sign up but dont stick around; activation rate; onboarding friction; retention metrics.
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.
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.
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.
SKILL.md names no scripts, command-line tools or credentials: Improve Retention is instructions for the agent only.
SKILL.md names 1 domain. As links in the text: amazon.com. 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.
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.
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.
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.
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.