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Agent skill

Surge Retention

by jeremylongshore in jeremylongshore/tons-of-skills-marketplace

Retention diagnosis + intervention plan — analyze the retention curve, identify the primary drop-off point, and produce a specific intervention plan with expected impact.

MITAuto-check: notesMarketing & SEO

Install Surge Retention

skills CLI
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill surge-retention -a claude-code

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

GitHub CLI
$ gh skill install jeremylongshore/tons-of-skills-marketplace surge-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/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/ai-agency/tonone/skills/surge-retention .claude/skills/surge-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
surge-retention
GitHub stars
2.8k
Token cost
~2.4k tokens
SKILL.md length
712 words
Files
2
Skills in repo
3,342
Repo updated
First seen
Licence
MIT

At a glance

Retention diagnosis + intervention plan — analyze the retention curve, identify the primary drop-off point, and produce a specific intervention plan with expected impact.

  • Works in 8 steps: Detect Environment → Gather the Retention Signal → Diagnose the Retention Curve → …
  • Asked to improve retention
  • SKILL.md covers Operating Principle, Step 0: Detect Environment, Step 1: Gather the Retention… and Step 2: Diagnose the Retention…, plus 6 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Surge Retention is an agent skill from jeremylongshore/tons-of-skills-marketplace. Retention diagnosis + intervention plan — analyze the retention curve, identify the primary drop-off point, and produce a specific intervention plan with expected impact. Use when asked to "improve retention", "why are users churning", "build a retention playbook", "reduce churn", "win-back campaign", or "users aren't coming back".

Its SKILL.md is about 2.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `.claude-plugin/plugin.json`).

It sits in Marketing & SEO, covering Referral and retention marketing. The repository describes itself as: Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com. The licence is MIT.

When your agent uses it

  • Asked to improve retention
  • Why are users churning
  • Build a retention playbook
  • Win-back campaign

Example prompts

  • “improve retention”
  • “why are users churning”
  • “build a retention playbook”
  • “/surge-retention”

Requirements

  • Pre-approved tools (allowed-tools): Read, Write, Edit, Bash, Glob, Grep, WebFetch, WebSearch, Task, TodoWrite, AskUserQuestion

Workflow steps

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

  1. Detect Environment
  2. Gather the Retention Signal
  3. Diagnose the Retention Curve
  4. Identify Churn Drivers
  5. Design the Intervention Plan
  6. Design the Habit Loop
  7. Prioritize and Score
  8. Deliver

What it can do on your machine

Read from SKILL.md and the folder at commit cfae287. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Write
    • Edit
    • Bash
    • Glob
    • Grep
    • WebFetch
    • WebSearch
    • Task
    • TodoWrite

    …and 1 more on the same allowed-tools line.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are bash).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    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

Surge Retention loads about 2.4k tokens when it runs. Until then it costs about 87 tokens; SKILL.md has 712 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~87
When it runs · the whole SKILL.md, loaded when a task matches
~2.4k

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: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
    allowed-tools: Read, Write, Edit, Bash, Glob, Grep, WebFetch, WebSearch, Task, TodoWrite, AskUserQuestion

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 jeremylongshore/tons-of-skills-marketplace at commit cfae287, republished under its MIT licence (© jeremylongshore). 712 words, ~2,434 tokens.

Download SKILL.mdSave it as .claude/skills/surge-retention/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
surge-retention
description
Retention diagnosis + intervention plan — analyze the retention curve, identify the primary drop-off point, and produce a specific intervention plan with expected impact. Use when asked to "improve retention", "why are users churning", "build a retention playbook", "reduce churn", "win-back campaign", or "users aren't coming back".
allowed-tools
Read, Write, Edit, Bash, Glob, Grep, WebFetch, WebSearch, Task, TodoWrite, AskUserQuestion
version
0.6.4
author
tonone-ai <hello@tonone.ai>
license
MIT

Retention Diagnosis + Intervention Plan

You are Surge — the growth engineer on the Product Team. Retention before acquisition. Diagnose first, prescribe second. Produce a plan, not a list of options.

Follow the output format defined in docs/output-kit.md — 40-line CLI max, box-drawing skeleton, unified severity indicators, compressed prose.

Operating Principle

A retention curve that never flattens means no retained core exists — that is a PMF problem, not a retention tactics problem. No amount of win-back emails fixes PMF. Identify which problem you're actually solving before prescribing anything.

Retention problems have three shapes:

  • Early drop-off (D1–D7): Users leave before reaching value. This is an activation problem disguised as a retention problem. Fix onboarding first.
  • Mid drop-off (D7–D30): Users activated but didn't form a habit. Return triggers are missing or the habit loop is weak.
  • Late drop-off (D30+): Users retained but eventually exhausted the product's value. Product needs to grow with the user — depth, collaboration, integrations.

Identify the shape. The shape determines the intervention category.

Step 0: Detect Environment

Scan for retention-related infrastructure before asking questions.

bash
# Email / notification infra
grep -rl "sendgrid\|resend\|postmark\|ses\|email\|notification\|cron\|schedule" \
  --include="*.ts" --include="*.tsx" --include="*.py" --include="*.go" . 2>/dev/null | head -10

# Retention / cohort tracking
grep -rl "retention\|churn\|D7\|D30\|cohort\|reactivat\|win.back" \
  --include="*.ts" --include="*.tsx" --include="*.py" . 2>/dev/null | head -10

# Cancellation / offboarding flow
grep -rl "cancel\|downgrade\|offboard\|delete.account\|churn.survey" \
  --include="*.ts" --include="*.tsx" --include="*.py" . 2>/dev/null | head -10

Note what exists. This shapes which interventions are feasible to ship quickly.

Step 1: Gather the Retention Signal

Ask for or derive from available data:

Quantitative (get numbers if they exist):

  • D1 / D7 / D30 / D90 retention rates
  • Retention curve shape — does it flatten or go to zero?
  • Activation rate — what % of signups complete the core action?
  • Usage frequency of retained vs churned users in the 7 days before churn

Qualitative (if available):

  • Churn survey responses — what do leaving users say?
  • Support tickets that precede cancellation
  • Actions churned users never took (vs actions retained users always took)

If no data is available, state the assumption and proceed. Don't stall waiting for perfect data.

Step 2: Diagnose the Retention Curve

Classify the drop-off pattern and its root cause:

PatternShapeRoot CauseIntervention Category
Early drop-offSteep fall D1–D7, then plateauActivation failure — users never found valueFix onboarding, reduce time-to-aha
Mid drop-offGradual fall D7–D30Habit not formed — no return triggerHabit loop design, re-engagement triggers
Late drop-offGood early, decline D30–D90+Value exhaustion — product doesn't grow with userDepth features, expansion paths, collaboration
No plateauCurve never flattensNo retained core — PMF not confirmedStop retention tactics; address PMF first

State the diagnosis explicitly. One primary pattern. If mixed, call the dominant one.

Show full SKILL.md (327 more words)Show less

Step 3: Identify Churn Drivers

Map available signal to driver categories. Prioritize by volume — address what's causing the most churn, not what's easiest to fix.

DriverSignalAddressable?
Activation failureNever used core feature; left in first weekYes — onboarding fix
Habit not formedLow session frequency; no return trigger hitYes — trigger design
Product gap"It doesn't do X" in churn surveysDepends on roadmap
Price / value mismatch"Not worth it"; downgrade to freeYes — value communication, tier redesign
Competition"Switched to [X]"Yes — differentiation, win-back
External / situationalBudget cut, job change, project endedNo — can't fix, can reduce with annual plans

Rank the top 1–2 drivers. These get interventions. Everything else is noise until the top drivers are addressed.

Step 4: Design the Intervention Plan

For each driver, produce a specific intervention — not a category, a specific action.

Activation-failure interventions (D0–D7):

State the trigger, the intervention, the message framing, and the implementation path:

Trigger:      User has not completed [core action] within 24 hours of signup
Intervention: In-app prompt on next session + Day 1 email
Message:      "You're one step from [specific value outcome] — here's how"
Ship path:    [email in Customer.io / in-app in [framework]] — estimated effort: [S/M/L]

Habit-formation interventions (D7–D30):

Trigger:      User has not returned in 5 days after activation
Intervention: Day 5 email with personalized usage summary or next-action prompt
Message:      Value reminder framing — show what they accomplished, suggest next action
Ship path:    [tool] — estimated effort: [S/M/L]

At-risk interventions (D14–D30):

Trigger:      Usage drops >50% week-over-week for an activated user
Intervention: In-app re-engagement prompt + offer for high-value accounts
Message:      Curiosity framing — "You haven't [action] recently. Can we help?"
Ship path:    [tool] — estimated effort: [S/M/L]

Win-back (D30+, churned):

Trigger:      Cancellation or 30+ days of inactivity
Sequence:     3 emails max over 30 days. More than 3 harms brand.
Email 1 (Day 0):  "What happened?" — single question, no hard sell
Email 2 (Day 14): New value — "Since you left, we added [X]"
Email 3 (Day 30): Final offer — specific incentive or close gracefully

Step 5: Design the Habit Loop

If mid-drop-off is the primary pattern, design or strengthen the core habit loop. The investment leg is what makes leaving costly — don't skip it.

Trigger    → [What reminds the user to return? External or internal?]
    ↓
Action     → [The core action the user takes when they return]
    ↓
Reward     → [The value delivered — variable reward is stickier than fixed]
    ↓
Investment → [What the user puts in that increases switching cost]
             Examples: saved data, trained models, team history, integrations, content

If no investment leg exists, the product has low switching cost. That is a product problem — flag it.

Step 6: Prioritize and Score

Score each intervention. Ship in priority order. Don't ship everything at once.

InterventionDriver addressedUsers affectedD30 lift estimateEffortPriority
[Intervention 1][driver][N or %]+[X]ppS/M/LP0
[Intervention 2][driver][N or %]+[X]ppS/M/LP1
[Intervention 3][driver][N or %]+[X]ppS/M/LP2

P0 = ship this week. P1 = ship this sprint. P2 = backlog.

Step 7: Deliver

Output using the format below. Make specific calls — don't present options.

╔══════════════════════════════════════════════════════╗
║  RETENTION DIAGNOSIS                                 ║
╠══════════════════════════════════════════════════════╣
║  D7: [%]  D30: [%]  D90: [%]                        ║
║  Curve: [early drop / mid drop / late drop / no PMF] ║
║  Primary churn driver: [driver]                      ║
╚══════════════════════════════════════════════════════╝

INTERVENTION PLAN

P0 — Ship this week:
  Trigger:      [specific trigger]
  Intervention: [specific action]
  Estimated impact: +[X]pp D30 retention over [N] weeks

P1 — Ship this sprint:
  Trigger:      [specific trigger]
  Intervention: [specific action]

HABIT LOOP
  Trigger → Action → Reward → Investment
  [specific for this product]

GAP FLAG (if any):
  [Investment leg missing / PMF signal weak / no churn survey data]

SINGLE HIGHEST-LEVERAGE ACTION THIS WEEK:
  [One sentence. Specific. Actionable.]

Delivery

If output exceeds the 40-line CLI budget, invoke /atlas-report with the full findings. The HTML report is the output. CLI is the receipt — box header, one-line verdict, top 3 findings, and the report path. Never dump analysis to CLI.

© jeremylongshore, 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 1 other file in plugins/ai-agency/tonone/skills/surge-retention of jeremylongshore/tons-of-skills-marketplace.

  • SKILL.md
  • .claude-plugin/plugin.json

Open the folder on GitHubat commit cfae287

Compare with similar skills

Surge 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.

Surge Retention compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Surge Retention this skilljeremylongshore/tons-of-skills-marketplace2.8k—~2.4kAutomated safety check: NotesMIT
Referralscoreyhaines31/marketingskills54k2 repos~2.6kAutomated safety check: PassMIT
Referral Programfreekmurze/dotfiles1k17 repos~1.8kAutomated safety check: PassNone
Churn Preventionrongxinzy/RongxinAI1543 repos~2.6kAutomated safety check: PassMIT
100m Leadsgetagentseal/founder-playbook729—~2.3kAutomated safety check: PassMIT
Churn Preventionfreekmurze/dotfiles1k13 repos~4.4kAutomated safety check: PassNone

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Categories

Questions about Surge Retention

What does Surge Retention do?

Retention diagnosis + intervention plan — analyze the retention curve, identify the primary drop-off point, and produce a specific intervention plan with expected impact. Surge Retention is an agent skill from jeremylongshore/tons-of-skills-marketplace. Retention diagnosis + intervention plan — analyze the retention curve, identify the primary drop-off point, and produce a specific intervention plan with expected impact.

When should I use Surge Retention?

Surge Retention fits situations like: asked to improve retention; why are users churning; build a retention playbook; win-back campaign.

How do I install Surge Retention in Claude Code?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill surge-retention -a claude-code`. Or copy the skill folder (plugins/ai-agency/tonone/skills/surge-retention in jeremylongshore/tons-of-skills-marketplace) into .claude/skills/surge-retention in your project. Claude Code loads it when a task matches its description.

How do I install Surge Retention in Codex?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill surge-retention -a codex`. Or copy the skill folder (plugins/ai-agency/tonone/skills/surge-retention in jeremylongshore/tons-of-skills-marketplace) into .agents/skills/surge-retention in your project. Codex loads it when a task matches its description.

Can I use Surge 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 jeremylongshore/tons-of-skills-marketplace --skill surge-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/surge-retention, .gemini/skills/surge-retention, .github/skills/surge-retention and .opencode/skills/surge-retention in your project.

What does Surge Retention need to run?

SKILL.md names no scripts, command-line tools or credentials: Surge Retention is instructions for the agent only. Its frontmatter pre-approves these tools: Read, Write, Edit, Bash, Glob, Grep, WebFetch, WebSearch, Task, TodoWrite, AskUserQuestion.

Does Surge Retention access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Surge Retention safe to install?

Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Surge Retention use?

Surge 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 Surge Retention use?

About 2.4k tokens (SKILL.md is roughly 9.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Surge Retention?

Skills that share tags, products or a category with Surge Retention: Referrals (coreyhaines31/marketingskills, 54k stars), Referral Program (freekmurze/dotfiles, 1k stars), Churn Prevention (rongxinzy/RongxinAI, 154 stars) and 100m Leads (getagentseal/founder-playbook, 729 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Surge Retention?

jeremylongshore (a GitHub user) maintains it in jeremylongshore/tons-of-skills-marketplace, which has 2,827 GitHub stars. The repository holds 3,342 skills in this directory. The repository was last updated on October 10, 2026.

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