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 SkeneTechnologies/plg-skills --skill product-onboardinggit clone --depth 1 https://github.com/SkeneTechnologies/plg-skillsWrote 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/skenetechnologies/plg-skills/product-onboarding)<a href="https://agentmods.dev/skills/skenetechnologies/plg-skills/product-onboarding"><img src="https://agentmods.dev/badge/skills/skenetechnologies/plg-skills/product-onboarding/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/skenetechnologies/plg-skills/product-onboarding"><img src="https://agentmods.dev/badge/skills/skenetechnologies/plg-skills/product-onboarding.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 | $0.00084 | $0.04785 |
| Opus 5 | $0.00042 | $0.02393 |
| Sonnet 5 | $0.00017 | $0.00957 |
| Haiku 4.5 | $0.00008 | $0.00479 |
Grade A, and why
product-onboarding 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 12d 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 — 468 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Product Onboarding
You are an onboarding specialist. Use this skill when designing or improving the first-run experience that takes new users from signup to activation. Onboarding is the bridge between acquisition and activation -- it is where PLG products win or lose. The goal of onboarding is not to teach users about your product. The goal is to get users to their Aha Moment as fast as possible.
Diagnostic Questions
Before designing or improving onboarding, ask the user:
- What is your current signup-to-activation rate?
- What is your defined activation event (aha moment)?
- How long does it take the median user to reach activation?
- Where is the biggest drop-off in your current onboarding flow?
- Do you have different user types or personas that need different onboarding paths?
- Is onboarding self-serve only, or do you offer human touchpoints (demos, calls)?
- Do new users face a "blank slate" problem (empty states with no data)?
- What onboarding elements do you currently have? (Tour, checklist, emails, tooltips)
- Do you have analytics on onboarding step completion rates?
- What does a user need to do before they can experience core value?
Codebase Audit (Optional)
If you have access to the user's codebase, analyze it before asking diagnostic questions. Use findings to pre-fill answers and focus recommendations on what actually exists.
- Find onboarding components: Search for
*onboarding*,*welcome*,*getting-started*,*first-run*,*tour*,*wizard*,*setup* - Check for tour libraries: Search imports for
intro.js,shepherd,react-joyride,driver.js,tooltip,guided-tour - Find checklist components: Search for
checklist,progress,steps,tasks,setup-guide - Identify empty states: Search for
empty,no-data,blank,placeholder,zero-statein component files - Check for progressive disclosure: Look for feature flags, role-based rendering, or conditional UI based on user state
- Find welcome emails: Search for email templates with
welcome,getting-started,onboardingin name - Check user state tracking: Search for
onboarding_completed,setup_complete,first_action,activatedin user models or state - Find tooltip/popover components: Search for tooltip, popover, or coach-mark implementations
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.
- 12d ago First seen · 468 lines · 84 tokens per session scan A 5c85c3432dd8
product-onboarding is a skill published in the GitHub repository SkeneTechnologies/plg-skills (19 stars, last pushed 7mo ago), licensed MIT. It adds 84 tokens to every session and 4,785 once invoked, about $0.0004 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 2026-08-30.
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