onboard

onboard is a skill for Claude Code from MotWakorb/ai-agent-dev-team. It costs 47 tokens per session (6,187 once invoked), scanned A, original, MIT.

A project-onboarding workflow that reviews an unfamiliar codebase, its documentation, infrastructure, and version history through ten specialist viewpoints.

In plain words
What is it for?
Assessing an existing project, finding gaps and risks, and creating an initial work backlog.
Why use it?
It gives a team a shared starting picture of how the project works, what is missing, and what could go wrong.

Skill for Claude Code

Written for Claude Code: user-invocable in frontmatter. Also seen: reads .claude/ paths; mentions CLAUDE.md.

Good fit Assessing an existing project, finding gaps and risks, and creating an initial work backlog.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/motwakorb/ai-agent-dev-team/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.

Any agent
npx skills add MotWakorb/ai-agent-dev-team --skill onboard
Clone the repo
git clone --depth 1 https://github.com/MotWakorb/ai-agent-dev-team

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/skills/motwakorb/ai-agent-dev-team/onboard/github.svg)](https://agentmods.dev/skills/motwakorb/ai-agent-dev-team/onboard)
Your own site
<a href="https://agentmods.dev/skills/motwakorb/ai-agent-dev-team/onboard"><img src="https://agentmods.dev/badge/skills/motwakorb/ai-agent-dev-team/onboard/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.

agentmods 80×15 button for onboard

Your own site · 80×15
<a href="https://agentmods.dev/skills/motwakorb/ai-agent-dev-team/onboard"><img src="https://agentmods.dev/badge/skills/motwakorb/ai-agent-dev-team/onboard.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 47 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 6,187 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 $0.00047 $0.06187
Opus 5.5 $0.00019 $0.02475
Sonnet 5.5 $0.00009 $0.01237
Haiku 4.5 $0.00005 $0.00619

Measured 2mo ago against content hash ca275c06a41b, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, 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 2mo 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.

onboard/SKILL.md · 574 lines

How it starts

The opening of the file, as written. The whole thing — 574 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Project Onboarding

This skill brings the full team up to speed on an existing project they've never seen. Each persona assesses the project from their domain, producing a baseline understanding with gaps, risks, and recommendations. The lens for every assessment is user value: is this project delivering value to its users, and what's getting in the way?

Model Selection

When spawning agents, pass model: explicitly per _shared/orchestration.md (Agent Model Selection). For this skill:

  • IT Architect (leads component identification + tier proposal): opus — needs reasoning to draft the component list and propose tiers from observable signals
  • Other personas: sonnet

Onboarding runs before COMPONENTS.md exists, so no tier modulation applies. Use the assignments above as written.

Process

Step 0: Gather Project Context

Before spawning agents, collect what's available:

Project structure:

find . -type f -name "*.md" -o -name "*.json" -o -name "*.yaml" -o -name "*.yml" -o -name "*.toml" -o -name "*.tf" -o -name "*.py" -o -name "*.ts" -o -name "*.js" | head -100

Documentation (read, not just list):

cat README.md 2>/dev/null
cat CLAUDE.md 2>/dev/null
cat CONTRIBUTING.md 2>/dev/null
cat DEVELOPMENT.md 2>/dev/null
cat SECURITY.md 2>/dev/null
cat CHANGELOG.md 2>/dev/null | head -50
ls docs/ adrs/ docs/adrs/ runbooks/ 2>/dev/null

Git history — activity, contributors, releases:

git log --oneline -20 2>/dev/null
git shortlog -sn --since="3 months ago" 2>/dev/null
git tag -l --sort=-version:refname | head -10 2>/dev/null

Stack — packages, toolchain versions:

cat package.json 2>/dev/null | head -40
cat pyproject.toml 2>/dev/null | head -40
cat requirements.txt 2>/dev/null | head -20
cat go.mod 2>/dev/null | head -10
cat .tool-versions .nvmrc .python-version mise.toml 2>/dev/null

Infrastructure & service topology (read, not just list):

cat docker-compose*.yml 2>/dev/null
cat Dockerfile* 2>/dev/null
ls -la terraform/ infrastructure/ deploy/ ansible/ 2>/dev/null
cat .env.example 2>/dev/null

Read the full file on GitHub · 574 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. 2mo ago First seen · 574 lines · 47 tokens per session scan A ca275c06a41b

Subscribe to this mod's changes

onboard is a skill published in the GitHub repository MotWakorb/ai-agent-dev-team (2 stars, last pushed 2mo ago), licensed MIT. It adds 47 tokens to every session and 6,187 once invoked, about $0.0002 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 2026-08-31.

Related

onboard compared with skills from other repositories

onboard next to 6 skills from other repositories
ModTypeStarsLast pushLicenceScanTokensWorks with
onboardMotWakorb/ai-agent-dev-teamSkill22mo agoMITA47Claude Code
imagegenopenai/codexSkill134ktodayApache-2.0A113Codex
playwright-climicrosoft/playwrightSkill99ktodayApache-2.0A19Claude Code
local-ai-agentsmicrosoft/ai-agents-for-beginnersSkill79ktodayMITA200Claude Code, Codex
systematic-debuggingobra/superpowersSkill314k3d agoMITA21Claude Code
next-cache-components-adoptionvercel/next.jsSkill143kyesterdayMITA95Claude Code
next-partial-prefetching-adoptionvercel/next.jsSkill143kyesterdayMITA103Claude Code