onboard

onboard is a command for Claude Code from smicolon/ai-kit. It costs 23 tokens per session (2,293 once invoked), scanned A, original, MIT.

An interactive onboarding guide that asks about an engineer's experience, examines the project, and creates personalized guidance for starting work in it.

In plain words
What is it for?
It assesses a developer's background, identifies unfamiliar areas, explains the project, and prepares a task-specific guide or cheat sheet.
Why use it?
It shortens the time needed to understand an unfamiliar codebase by connecting project details with the engineer's existing skills and gaps.

Command for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: mentions CLAUDE.md; names the AskUserQuestion tool.

Good fit It assesses a developer's background, identifies unfamiliar areas, explains the project, and prepares a task-specific guide or cheat sheet.

Compare 6 commands from other repositories ↓
Install with agentmods
npx agentmods add commands/smicolon/ai-kit/onboard
Install

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.

Clone the repo
git clone --depth 1 https://github.com/smicolon/ai-kit

Made for: Claude Code.

Wrote 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.

agentmods badge for onboard

README.md
[![agentmods](https://agentmods.dev/badge/commands/smicolon/ai-kit/onboard.svg)](https://agentmods.dev/commands/smicolon/ai-kit/onboard)
Your own site
<a href="https://agentmods.dev/commands/smicolon/ai-kit/onboard"><img src="https://agentmods.dev/badge/commands/smicolon/ai-kit/onboard.svg" alt="Measured on agentmods" height="20"></a>
Per session 23 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,293 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00023 $0.02293
Opus 5 $0.00012 $0.01146
Sonnet 5 $0.00005 $0.00459
Haiku 4.5 $0.00002 $0.00229

Measured 4d ago against content hash bc44de198747, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

onboard 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 4d 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.

packs/onboard/commands/onboard.md · 314 lines

How it starts

The opening of the file, as written. The whole thing — 314 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Engineer Onboarding

Run a guided onboarding flow that personalizes project guidance based on the engineer's background and their first task.


Steps

1. Parse Arguments

Extract from user input:

  • --quick: Skip skill assessment, assume mid-level generalist (optional)
  • --task: Pre-specify first task to skip task question (optional)

2. Introduction

Briefly explain what will happen:

Welcome! I'll get you up to speed on this project in a few minutes.

Here's how this works:
1. A few questions about your background (so I don't over-explain things you know)
2. I'll analyze the project automatically
3. You'll get personalized guidance + a cheat sheet

Let's start.

3. Engineer Assessment (skip if --quick)

Ask these core questions using AskUserQuestion:

Question 1 - Primary Stack: "What's your primary language/framework and roughly how long have you been using it?"

Question 2 - Other Skills: "What other languages or frameworks are you comfortable with?"

Question 3 - New Territory: "Looking at this project, what feels completely new or unfamiliar to you?"

Adaptive Follow-ups (only ask if gaps detected):

After analyzing the answers, ask follow-ups ONLY for detected gaps:

  • If the project uses frontend tech and engineer is backend-only: "Any experience with component-based UI frameworks (React, Vue, etc.)?"

  • If the project uses backend tech and engineer is frontend-only: "Have you worked with ORMs, REST APIs, or database design?"

  • If the project has tests and engineer didn't mention testing: "How comfortable are you with writing tests / TDD?"

  • If the project uses TypeScript and engineer only mentioned JavaScript: "How's your TypeScript experience — types, generics, strict mode?"

Maximum 2 follow-up questions. Keep the assessment fast.

4. Project Analysis (automatic)

Analyze the project silently. Do NOT ask the engineer anything here.

4a. Detect Project Type:

# Frontend
[ -f "package.json" ] && grep -q '"next"' package.json && echo "nextjs"
[ -f "package.json" ] && grep -q '"nuxt"' package.json && echo "nuxtjs"
[ -f "package.json" ] && grep -q "@tanstack/react-router" package.json && echo "tanstack-router"
[ -f "package.json" ] && grep -q '"hono"' package.json && echo "hono"

# Backend
[ -f "manage.py" ] && echo "django"
[ -f "package.json" ] && grep -q "@nestjs/core" package.json && echo "nestjs"

# Mobile
[ -f "pubspec.yaml" ] && echo "flutter"

# Auth
[ -f "package.json" ] && grep -q '"better-auth"' package.json && echo "better-auth"

Read the full file on GitHub · 314 lines

Changes

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.

  1. 4d ago First seen · 314 lines · 23 tokens per session scan A bc44de198747

Subscribe to this mod's changes

onboard is a command published in the GitHub repository smicolon/ai-kit (6 stars, last pushed 4d ago), licensed MIT. It adds 23 tokens to every session and 2,293 once invoked, about $0.0001 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 2026-09-03.