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 event4u-app/agent-config --skill onboarding-designgit clone --depth 1 https://github.com/event4u-app/agent-configWrote 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/event4u-app/agent-config/onboarding-design)<a href="https://agentmods.dev/skills/event4u-app/agent-config/onboarding-design"><img src="https://agentmods.dev/badge/skills/event4u-app/agent-config/onboarding-design/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/event4u-app/agent-config/onboarding-design"><img src="https://agentmods.dev/badge/skills/event4u-app/agent-config/onboarding-design.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 | $0.00040 | $0.01842 |
| Opus 5 | $0.00020 | $0.00921 |
| Sonnet 5 | $0.00008 | $0.00368 |
| Haiku 4.5 | $0.00004 | $0.00184 |
Grade A, and why
onboarding-design 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 8d 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 — 167 lines — stays where its author put it; the contents beside it link to each section on GitHub.
onboarding-design
When to use
- New accounts churn inside their first 30 days and the team cannot name which onboarding milestone they failed to reach — drop-off is treated as a single number, not a stage-by-stage signal.
- A new segment is being onboarded against an onboarding flow built for a previous segment — the milestones likely do not match the new segment's switch-event shape.
- Time-to-first-value is "days, maybe weeks" — the answer needs to be a number with a falsifiable definition, not a sentiment.
Do NOT use to onboard employees (that is the Wing-4
employee-onboarding program — different audience, different
contract), diagnose long-cycle churn (route to
churn-prevention), or run the full visitor → paid funnel (route
to funnel-analysis).
Cognition cluster
- Mental model 14 — Meadows leverage points. Onboarding is a
high-leverage system: a change in the milestone definition
reshapes retention more than a change in the welcome email. Pick
the leverage point — milestone definition over surface polish.
See
docs/contracts/mental-models.md§ 14. - Mental model 16 — Leading vs. lagging indicators.
Time-to-first-value and milestone-completion are leading; D30
retention is lagging. Onboarding decisions built on lagging
signals can only confirm churn after it lands. See
mental-models.md§ 16. - Mental model 13 — Occam's razor. When new accounts drop off,
the simpler explanation usually wins: "the first milestone is
too far from the buyer's job to complete in one session" beats
"users do not understand our value proposition." Pick the
simpler explanation; it changes the move. See
mental-models.md§ 13. - Context-spine — product + customer-segment + funnel-stage.
Read the product slot for what the segment can actually
configure unattended, the customer-segment slot for the
segment's job and switch-event, and the funnel-stage slot for
where activation sits relative to signup and paid. See
context-spine.
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.
- 8d ago First seen · 167 lines · 40 tokens per session scan A 401070fcd847
onboarding-design is a skill published in the GitHub repository event4u-app/agent-config (10 stars, last pushed today), licensed MIT. It adds 40 tokens to every session and 1,842 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 2026-09-04.
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