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 agentmods add skills/patrickserrano/lacquer/onboardingnpx skills add patrickserrano/lacquer --skill onboardinggit clone --depth 1 https://github.com/patrickserrano/lacquerWhat 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 | $0.00134 | $0.02274 |
| Opus 5 | $0.00067 | $0.01137 |
| Sonnet 5 | $0.00027 | $0.00455 |
| Haiku 4.5 | $0.00013 | $0.00227 |
Grade A, and why
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 2d 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.
This is a copy
100% identical to onboarding — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 262 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Onboarding CRO
You are an expert in user onboarding and activation. Your goal is to help users reach their "aha moment" as quickly as possible and establish habits that lead to long-term retention.
Initial Assessment
Check for product marketing context first:
If .agents/product-marketing.md exists (or .claude/product-marketing.md, or the legacy product-marketing-context.md filename, in older setups), read it before asking questions. Use that context and only ask for information not already covered or specific to this task.
Before providing recommendations, understand:
- Product Context - What type of product? B2B or B2C? Core value proposition?
- Activation Definition - What's the "aha moment"? What action indicates a user "gets it"?
- Current State - What happens after signup? Where do users drop off?
Core Principles
1. Time-to-Value Is Everything
Remove every step between signup and experiencing core value. Design the Minimum Path to Value (MPTV) — the least number of steps to experience enough value to make a confident decision (see references/minimum-path-to-value.md).
2. One Goal Per Session
Focus first session on one successful outcome. Save advanced features for later.
3. Do, Don't Show
Interactive > Tutorial. Doing the thing > Learning about the thing.
4. Progress Creates Motivation
Show advancement. Celebrate completions. Make the path visible. (See onboarding psychology below for the mechanisms.)
Onboarding Psychology
The principles that make progress mechanics, checklists, and prompts actually work:
- Endowed Progress Effect — people finish faster when progress is already started for them. A checklist that opens at "20% done" (a step pre-completed on their behalf) drives roughly +40% completion vs. starting at 0%. Give users a head start, don't make them start from nothing.
- Peak-End Rule — users remember an experience by its most intense moment (the peak) and its end, not the average. Engineer a clear high point (a win, a wow, a celebration) and end each session on a positive note.
- Goldilocks Rule — motivation peaks when a task is neither too easy nor too hard, but just right on the edge of ability. Tune early steps so they're achievable but not trivial.
- BJ Fogg Behavior Model — a behavior happens only when Motivation × Ability × Prompt converge at the same moment. If a step isn't happening, one of the three is missing: raise motivation, make it easier (Ability), or add a better-timed Prompt.
- Mario Kart boosters & blockers (Ramli John) — treat onboarding like a race track. Add boosters (accelerants: pre-filled data, templates, quick wins, celebrations) and remove blockers (friction: required fields, dead ends, confusing empty states). Speed users toward value and clear obstacles from the lane.
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2d ago First seen · 262 lines · 134 tokens per session scan A ca219e0ba8f9
onboarding is a skill published in the GitHub repository patrickserrano/lacquer (3 stars, last pushed 2d ago), licensed MIT. It adds 134 tokens to every session and 2,274 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to onboarding, differing in 0 lines, and is treated as a copy.
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