retention-engagement

retention-engagement is a skill for Claude Code, Codex from liqiongyu/lenny_skills_plus. It costs 32 tokens per session (2,414 once invoked), scanned A, original, Apache-2.0.

A framework for deciding whether a meeting is needed, preparing it, guiding the discussion, recording decisions, and following up on actions.

In plain words
What is it for?
Use it to create agendas and pre-reading, facilitate decision or workshop meetings, improve recurring meetings, and track commitments.
Why use it?
It helps stop meetings from drifting, repeating status updates, or ending without clear ownership.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to create agendas and pre-reading, facilitate decision or workshop meetings, improve recurring meetings, and track commitments.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/liqiongyu/lenny_skills_plus/retention-engagement
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add liqiongyu/lenny_skills_plus --skill retention-engagement
Clone the repo
git clone --depth 1 https://github.com/liqiongyu/lenny_skills_plus

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for retention-engagement

README.md
[![agentmods](https://agentmods.dev/badge/skills/liqiongyu/lenny_skills_plus/retention-engagement/github.svg)](https://agentmods.dev/skills/liqiongyu/lenny_skills_plus/retention-engagement)
Your own site
<a href="https://agentmods.dev/skills/liqiongyu/lenny_skills_plus/retention-engagement"><img src="https://agentmods.dev/badge/skills/liqiongyu/lenny_skills_plus/retention-engagement/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for retention-engagement

Your own site · 80×15
<a href="https://agentmods.dev/skills/liqiongyu/lenny_skills_plus/retention-engagement"><img src="https://agentmods.dev/badge/skills/liqiongyu/lenny_skills_plus/retention-engagement.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 32 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,414 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00032 $0.02414
Opus 5 $0.00016 $0.01207
Sonnet 5 $0.00006 $0.00483
Haiku 4.5 $0.00003 $0.00241

Measured 9d ago against content hash ba00631f1ccc, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

retention-engagement scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/retention-engagement/SKILL.md · 153 lines

How it starts

The opening of the file, as written. The whole thing — 153 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Retention & Engagement

Scope

Covers

  • Diagnosing retention + engagement (cohorts/curves, frequency, segments, drop-offs)
  • Identifying the activation / “aha moment” and reducing time-to-value
  • Designing habit + re-engagement interventions (daily return, reminders, content loops)
  • Creating accruing value and ethical switching costs (“mounting loss”)
  • Turning insights into a prioritized experiment + measurement plan

When to use

  • “Improve retention / reduce churn”
  • “Increase engagement / DAU/WAU”
  • “Define our activation / aha moment”
  • “D1/D7 retention is low—fix onboarding and time-to-value”
  • “Create a retention experiment backlog and a 30/60/90 plan”

When NOT to use

  • You don’t have (or can’t assume) a stable value proposition / ICP (use problem-definition).
  • You’re primarily deciding pricing/packaging/paywalls (this skill can add retention context but won’t replace pricing work).
  • You need acquisition loop design (use designing-growth-loops).
  • You need to synthesize qualitative churn feedback before proposing experiments (use analyzing-user-feedback or interviews).
  • The problem is specifically first-time onboarding UX (signup flow, empty states, guided setup) rather than full-lifecycle retention (use user-onboarding).
  • You want to apply behavioral science frameworks (habit loops, nudge theory, loss aversion mechanics) as the primary lens rather than a retention metrics lens (use behavioral-product-design).
  • You need to determine whether you have product-market fit before optimizing retention (use measuring-product-market-fit).

Inputs

Minimum required

  • Product + target user/ICP and 1–2 key segments
  • Current stage (pre-PMF / early PMF / growth / mature)
  • Best-available baseline metrics (even rough):
    • retention (D1/D7/D30 or weekly cohort), churn, engagement (DAU/WAU/MAU), activation rate, time-to-value
  • Onboarding flow summary (steps/screens + where users drop)
  • Constraints: timebox, engineering/design capacity, allowed channels (email/push/in-app), privacy/legal/brand limits

Read the full file on GitHub · 153 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago First seen · 153 lines · 32 tokens per session scan A ba00631f1ccc

Subscribe to this mod's changes

retention-engagement is a skill published in the GitHub repository liqiongyu/lenny_skills_plus (52 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 32 tokens to every session and 2,414 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.