keep

keep is an agent for Claude Code from jeremylongshore/tons-of-skills-marketplace. It costs 59 tokens per session (2,872 once invoked), scanned A, original, MIT.

A customer-success systems assistant for building onboarding flows, customer health scores, expansion playbooks, and churn-prevention sequences. Customer health scores estimate whether an account is likely to succeed or leave.

In plain words
What is it for?
Designing onboarding, modeling customer health, creating retention and expansion playbooks, and building churn-prevention sequences.
Why use it?
It turns customer-success work into repeatable systems instead of relying on individual staff members. It helps teams identify struggling customers before they cancel.

Agent for Claude Code

Written for Claude Code: background in frontmatter. Also seen: model in frontmatter; names the TodoWrite tool; positional $N argument.

Part of the tonone plugin — 100 agents, 9 plugins shipped together

Good fit Designing onboarding, modeling customer health, creating retention and expansion playbooks, and building churn-prevention sequences.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/jeremylongshore/tons-of-skills-marketplace/keep
About the project

Tons of Skills is a model-agnostic marketplace that distributes reusable skills, plugins, agents, commands, hooks, and settings for coding-agent tools. It is intended for people who want to browse, install, and manage agent extensions, with Claude Code as its verified native harness. The catalogue entries are extensions provided by or associated with this marketplace.

jeremylongshore/tons-of-skills-marketplace · 2,717 stars · on GitHub · tonsofskills.com

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.

Clone the repo
git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace

Made for: Claude Code.

Or install tonone, the plugin that ships this one along with the rest of its 100 agents, 9 plugins.

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 keep

README.md
[![agentmods](https://agentmods.dev/badge/agents/jeremylongshore/tons-of-skills-marketplace/keep/github.svg)](https://agentmods.dev/agents/jeremylongshore/tons-of-skills-marketplace/keep)
Your own site
<a href="https://agentmods.dev/agents/jeremylongshore/tons-of-skills-marketplace/keep"><img src="https://agentmods.dev/badge/agents/jeremylongshore/tons-of-skills-marketplace/keep/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 keep

Your own site · 80×15
<a href="https://agentmods.dev/agents/jeremylongshore/tons-of-skills-marketplace/keep"><img src="https://agentmods.dev/badge/agents/jeremylongshore/tons-of-skills-marketplace/keep.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 59 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,872 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 $0.00059 $0.02872
Opus 5 $0.00030 $0.01436
Sonnet 5 $0.00012 $0.00574
Haiku 4.5 $0.00006 $0.00287

Measured 9d ago against content hash e68da8f3dec5, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

keep 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

  • keep — 88% identical, 30 lines differ
plugins/ai-agency/tonone/agents/keep.md · 201 lines

How it starts

The opening of the file, as written. The whole thing — 201 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are Keep — customer success engineer on the Product Team. Don't advise on customer success strategy. Design the onboarding flows, build the health scoring model, write the expansion playbook, ship the churn prevention sequence. Output that goes into production.

One rule above all: retention before expansion. Expanding unhealthy customers accelerates churn and destroys NRR. Fix the health signal first.

Communication

Respond terse. All technical substance stays — only filler dies. Follow output-kit protocol: compressed prose, no filler, fragments OK. Code/security/commits: normal English. See docs/output-kit.md for CLI skeleton, severity indicators, 40-line rule.

Operating Principle

Onboarding IS the product. A product that requires a CSM to succeed at onboarding is a product that doesn't work. Goal: every customer reaches first value moment without touching a human. Then CSM multiplies that, doesn't replace it.

The 0-to-$100M customer success path has three stages:

Stage 1 — $0 to $1M ARR: High-touch everything No playbook exists. Founder or first hire is in every onboarding call. Learn what success looks like for each customer. Map the activation sequence. Document the "aha moment" concretely. Every churn is an autopsy. Every expansion is studied. Goal: define what "healthy" means before you can score it.

Stage 2 — $1M to $10M ARR: Scalable success Segment customers by ARR tier and complexity. High-touch reserved for strategic accounts. Mid-tier gets structured digital journey (automated + human checkpoints). Self-serve for small accounts. Health score model built from Stage 1 learnings. Expansion motions run proactively against health signals — not reactively when renewal arrives.

Stage 3 — $10M to $100M ARR: NRR engine Net Revenue Retention becomes primary growth lever. At $50M+ ARR, 120% NRR means you grow 20% without adding a single new customer. CS is no longer cost center — it's revenue center. Expansion, cross-sell, and upsell are owned by CS. Churn rate is a board metric. CS team has quota.

Read the full file on GitHub · 201 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 · 201 lines · 59 tokens per session scan A e68da8f3dec5

Subscribe to this mod's changes

keep is an agent published in the GitHub repository jeremylongshore/tons-of-skills-marketplace (2,717 stars, last pushed today), licensed MIT. It adds 59 tokens to every session and 2,872 once invoked, about $0.0003 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.

Related

Other agents, from other repositories

Hospitality Guest Services

Comprehensive hospitality guest services specialist for hotels, resorts, restaurants, and event venues — covering reservations, check-in/check-out, concierge services, guest complaint resolution, loyalty program management, and post-stay follow-up to deliver exceptional guest experiences that drive loyalty and revenue.

SHAdd0WTAka/Zen-Ai-Pentest · 57 tokens

HR Onboarding

Comprehensive HR onboarding specialist for employee orientation, documentation management, compliance tracking, benefits enrollment, culture integration, and new hire support — delivering a seamless first-day-to-first-year experience that drives retention and productivity.

SHAdd0WTAka/Zen-Ai-Pentest · 44 tokens

Chief of Staff

Master coordinator for founders and executives — filters noise, owns processes, enforces consistency, routes decisions, and positions outputs for impact so the boss can think clearly.

SHAdd0WTAka/Zen-Ai-Pentest · 36 tokens

workflow-optimizer

Use this agent for optimizing human-agent collaboration workflows and analyzing workflow efficiency. This agent specializes in identifying bottlenecks, streamlining processes, and ensuring smooth handoffs between human creativity and AI assistance.

PMDevSolutions/Aurelius · 43 tokens

dx-optimizer

Developer Experience (DX) optimization specialist. Reduces onboarding time, automates repetitive tasks, and improves tooling so development stays fast and enjoyable. Use for workflow audits, tooling upgrades, and onboarding improvements.

NickCrew/Claude-Cortex · 44 tokens

rollback-agent

Reverts failed fix attempts. Resets git state and posts block comment to issue tracker.

asysta-act/agent-flow · 21 tokens