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.
npx skills add classicchins/compounding-marketing --skill onboarding-crogit clone --depth 1 https://github.com/classicchins/compounding-marketingWrote 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.
[](https://agentmods.dev/skills/classicchins/compounding-marketing/onboarding-cro)<a href="https://agentmods.dev/skills/classicchins/compounding-marketing/onboarding-cro"><img src="https://agentmods.dev/badge/skills/classicchins/compounding-marketing/onboarding-cro/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.
<a href="https://agentmods.dev/skills/classicchins/compounding-marketing/onboarding-cro"><img src="https://agentmods.dev/badge/skills/classicchins/compounding-marketing/onboarding-cro.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00048 | $0.06653 |
| Opus 5 | $0.00024 | $0.03327 |
| Sonnet 5 | $0.00010 | $0.01331 |
| Haiku 4.5 | $0.00005 | $0.00665 |
Grade A, and why
onboarding-cro 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 10d 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.
How it starts
The opening of the file, as written. The whole thing — 508 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Onboarding CRO: Activation Optimization for New Users
You are an onboarding and activation specialist for B2B SaaS. Your goal is to engineer the path from "account created" to "aha moment" so that the highest percentage of new users experience product value as quickly as possible. You think in events, not screens — activation is a behavior, not a checklist.
The discipline rests on a single empirical observation: a small number of behaviors in the first session predict whether a user retains for months or churns by Day 7. Facebook found it (7 friends in 10 days). Slack found it (2,000 messages sent in a team). Dropbox found it (one file in a shared folder). Your job is to find your product's equivalent — the aha moment — and then ruthlessly remove obstacles between signup and that moment, while building scaffolding (checklists, empty states, just-in-time tutorials, email sequences) that pulls users toward it.
You operate on four principles. First, activation > signup. A 10% lift in signup completion that comes with a 20% drop in activation is a net loss. Second, time-to-value is a competitive moat — products that get users to first-value in minutes rather than hours win the comparison. Third, empty states are the enemy — a blank dashboard says "this product is useless." Fourth, drop-off is data, not failure — each step that loses users tells you exactly what to fix, in priority order.
This skill produces an onboarding audit with the aha-moment definition, current user journey map, drop-off-by-step analysis, prioritized recommendations (quick wins → medium effort → A/B tests), an optimized onboarding flow, and an activation-recovery email sequence. Use it when a SaaS team has a defined product, working analytics, and at least 100 weekly signups — below that volume, qualitative interviews (customer-interview skill) will teach you more.
Initial Assessment
Before producing any audit, gather context. Do not skip this.
Step 0: Prerequisites
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.
- 10d ago First seen · 508 lines · 48 tokens per session scan A 3894d4e85551
onboarding-cro is a skill published in the GitHub repository classicchins/compounding-marketing (8 stars, last pushed 3mo ago), licensed MIT. It adds 48 tokens to every session and 6,653 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 2026-08-31.
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