onboarding

A command that writes first-day onboarding documentation in Markdown for a project repository.

In plain words
What is it for?
Use it to create onboarding instructions and project orientation material. HTML or PDF output is available only when specifically requested.
Why use it?
It gives new team members a written starting point for understanding and working in the project.

Command

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.

agentmods
npx agentmods add commands/avinava/document-design-system/onboarding
Clone the repo
git clone --depth 1 https://github.com/Avinava/document-design-system
Per session 32 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 134 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 83% copy Near-identical to another mod 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 $0.00032 $0.00134
Opus 5 $0.00016 $0.00067
Sonnet 5 $0.00006 $0.00027
Haiku 4.5 $0.00003 $0.00013

Measured yesterday against content hash bc516c3ef3d8, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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 yesterday.

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.

Origin

This is a copy

83% identical to adr — 6 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.

commands/onboarding.md · 12 lines

What it actually says

Use the writing-documents skill. Type slug: onboarding Load references/type-onboarding.md, references/writing.md, references/evidence.md. Default output is Markdown in the user's project at this type's conventional path. Do not assemble HTML, pick a theme, inline CSS, or run build_document.py unless the user asked for HTML, PDF, print, or designed output. If they did, also load references/output.md and core/.

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. yesterday First seen · 12 lines · 32 tokens per session scan A bc516c3ef3d8

Subscribe to this mod's changes

onboarding is a command published in the GitHub repository Avinava/document-design-system (2 stars, last pushed 7d ago), licensed MIT. It adds 32 tokens to every session and 134 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 83% identical to adr, differing in 6 lines, and is treated as a copy.