Agent skill · Code Review & Quality

expansion-retention

When the user wants to reduce churn, build expansion revenue, automate customer success, or optimize net revenue retention. Also use when the user mentions 'churn,' 'retention,' 'expansion revenue,' 'upsell,' 'NRR,' 'net revenue retention,' 'customer success,' 'land and expand,' 'closed-lost,' or 'renewal.' This skill covers expansion and retention systems from usage triggers through automated customer success. Do NOT use for technical implementation, code review, or software architecture.

tech-leads-clubgithub.com/tech-leads-clubGitHub ↗
claude-codecopilotcursorNOASSERTION
Install
npx skills add tech-leads-club/agent-skills --skill expansion-retention --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 22 KB
Bundled scripts: none
Version: 1.0.0
Path: packages/skills-catalog/skills/(gtm)/expansion-retention/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 4,983
Language: TypeScript
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

Review
written from the skill's own SKILL.md · Aug 5, 2026

What it does

Guides an agent to address expansion and retention strategies from usage-driven triggers to automated customer success, targeting churn reduction, expansion revenue, and NR R optimization.

How it works

  • Recommends starting with questions to infer current metrics and context if the user does not provide them.
  • Covers Net Revenue Retention as a growth lever with a defined formula and segment/pricing benchmarks.
  • Defines Land-and-Expand expansion triggers and in-product expansion mechanics, including a Usage Visibility Dashboard, contextual upgrade prompts, and team expansion flows.
  • Outlines expansion pricing architecture and metrics for tracking expansion performance.
  • Establishes a framework for Customer Health Scoring, with component weights, segment-specific adjustments, action cadences by score, and automated responses to churn signals.
  • Describes Product-Qualified Accounts (PQA) scoring, threshold actions, and routing rules for high-potential accounts.
  • Details Automated Onboarding Sequences with milestone targets and a multi-step email/sequence plan.
  • Specifies Closed-Lost Re-engagement tactics, cadence design across phases, and win-back segmentation scoring.
  • Includes Usage-Based Billing Optimization guidance, selection of usage metrics, and proactive cost alert patterns.
  • Concludes with Advocacy and Renewal Management tiers and activities aligned to customer advocacy.

When to use it

Used when the user aims to reduce churn, build expansion revenue, automate customer success, or optimize net revenue retention. It is suitable when mentions include churn, retention, expansion revenue, upsell, NRR, renewal, land and expand, or related terms. Not intended for technical implementation, code review, or software architecture.

What it can touch

  • Tools: claude-code, copilot, cursor
  • Applies automation concepts, health scoring, onboarding sequences, and expansion triggers that could be implemented via these agents.

Caveats

  • Content reflects guidance on expansion/retention systems and does not cover technical implementation details.
  • No promises about outcomes; conclusions are framed as approaches and frameworks.
From the SKILL.md

# Expansion & Retention Systems You are a GTM strategist specializing in post-sale revenue growth, churn prevention, and net revenue retention optimization. You help founders and revenue leaders build systems that turn existing customers into their largest growth engine - through usage-based expansion, automated customer success, health scoring, and closed-lost re-engagement. ## Before Starting Ask the user: 1. What is your current NRR? (Below 100% = contraction, 100-110% = stable, 110%+ = expanding) 2. What pricing model do you use? (Seat-based, usage-based, hybrid, flat-rate) 3. What does your customer segmentation look like? (SMB, mid-market, enterprise, mixed) 4. Do you have a customer success team or is CS handled by founders/AEs? 5. What is your primary churn reason? (Price, product gaps, competitor, no champion, low usage) 6. What tools are in your CS stack? (CRM, product analytics, CS platform, billing) If the user skips these, infer from context and state your assumptions clearly. --- ## 1. Net Revenue Retention: The Growth Multiplier NRR measures whether your existing customer base is growing or shrinking before adding any new logos. ### NRR Formula ``` NRR = (Starting MR

What's inside
Steps it walks through
  1. Before Starting
  2. 1. Net Revenue Retention: The Growth Multiplier
  3. NRR Formula
  4. 2025-2026 NRR Benchmarks by Segment
  5. NRR Benchmarks by Pricing Model
  6. NRR Improvement Decision Framework
  7. 2. Land-and-Expand: Consumption-Based Upsell Triggers
  8. Expansion Trigger Matrix
  9. In-Product Expansion Mechanics
  10. Expansion Pricing Architecture
  11. Land-and-Expand Metrics
  12. 3. Customer Health Scoring
  13. Health Score Components
  14. Health Score by Segment
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About this skill
What does the expansion-retention skill do?

When the user wants to reduce churn, build expansion revenue, automate customer success, or optimize net revenue retention. Also use when the user mentions 'churn,' 'retention,' 'expansion revenue,' 'upsell,' 'NRR,' 'net revenue retention,' 'customer success,' 'land and expand,' 'closed-lost,' or 'renewal.' This skill covers expansion and retention systems from usage triggers through automated customer success. Do NOT use for technical implementation, code review, or software architecture.

How do I install it?

Run `npx skills add tech-leads-club/agent-skills --skill expansion-retention --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From tech-leads-club/agent-skills, a repository with 4,983 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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