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 ommakes/Skills --skill onboarding-flowgit clone --depth 1 https://github.com/ommakes/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/ommakes/skills/onboarding-flow)<a href="https://agentmods.dev/skills/ommakes/skills/onboarding-flow"><img src="https://agentmods.dev/badge/skills/ommakes/skills/onboarding-flow/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/ommakes/skills/onboarding-flow"><img src="https://agentmods.dev/badge/skills/ommakes/skills/onboarding-flow.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 | $0.00153 | $0.03238 |
| Opus 5.5 | $0.00061 | $0.01295 |
| Sonnet 5.5 | $0.00031 | $0.00648 |
| Haiku 4.5 | $0.00015 | $0.00324 |
Grade A, and why
onboarding-flow 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 19d 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 — 243 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Onboarding Flow
A skill for designing onboarding for two very different contexts. SaaS/web onboarding and consumer/mobile onboarding fail for opposite reasons if you cross the patterns: block a SaaS user behind a linear wizard and they bounce before seeing the product; let a consumer app skip the personalization quiz and you lose the sign-up's whole reason for existing. Pick the right one before you design or evaluate anything.
This skill defines the sequence and screen types. It is not a copywriting or styling skill:
- Every word that appears on screen (headlines, button labels, quiz questions, permission copy, checklist item text) routes to the righter skill. Don't guess at wording here.
- Every structural/visual decision (spacing, components, tokens, animation, accessibility) routes to vois-patterns → vois-components → vois-tokens, in that order.
- This skill sits above both: it tells you which screens exist and in what order (or should); righter tells you what words go on them; vois tells you how they're built.
Two Modes
Mode 1: Evaluate an Existing Flow
- Get the flow in front of you. Screenshots, a Figma/Mobbin link, or a plain description of the screen-by-screen sequence. If it's incomplete, say what's missing rather than guessing at unseen screens.
- Determine the shape using the decision tree below — SaaS companion checklist or consumer linear sequence. An existing flow that uses the wrong shape for its product type is itself a finding, not something to route around.
- Read the matching reference file and walk the flow screen by screen against every rule
idindata/onboarding-rules.jsonfor that shape, plus the fiveUNIV-*rules. If the flow states or implies its activation event (see Mode 2 step 2), treat any screen that doesn't move toward it as a candidate cut even when it doesn't fail a specific numbered rule. - Output in the Review format below. Don't rewrite copy or restyle components yourself — flag copy issues for righter and structural issues for vois-patterns, cite what should be checked there, and stop.
What ships with it
6 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.
- 19d ago First seen · 243 lines · 153 tokens per session scan A 420146508a2a
onboarding-flow is a skill published in the GitHub repository ommakes/Skills (21 stars, last pushed 6d ago), licensed MIT. It adds 153 tokens to every session and 3,238 once invoked, about $0.0006 per session on Opus 5.5. 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 2026-09-27.
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