Onboarding Interview

Onboarding Interview is an agent for coding agents from kouroshez/coding-os. It costs 3 tokens per session (1,039 once invoked), scanned A, original, Apache-2.0.

An onboarding agent that interviews a project user and drafts the essential product documents under the project's docs folder. It adjusts the amount of documentation to the project's size and type.

In plain words
What is it for?
Use it after project setup to create a vision note, product requirements, constraints, or an architecture outline.
Why use it?
It turns missing or vague project knowledge into written guidance that other development work can rely on.

Agent

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 agents/kouroshez/coding-os/onboarder
Clone the repo
git clone --depth 1 https://github.com/kouroshez/coding-os

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 Onboarding Interview

README.md
[![agentmods](https://agentmods.dev/badge/agents/kouroshez/coding-os/onboarder.svg)](https://agentmods.dev/agents/kouroshez/coding-os/onboarder)
Your own site
<a href="https://agentmods.dev/agents/kouroshez/coding-os/onboarder"><img src="https://agentmods.dev/badge/agents/kouroshez/coding-os/onboarder.svg" alt="Measured on agentmods" height="20"></a>
Per session 3 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,039 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00003 $0.01039
Opus 5 $0.00002 $0.00519
Sonnet 5 $0.00001 $0.00208
Haiku 4.5 $0.00000 $0.00104

Measured yesterday against content hash 7590496b0173, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

Onboarding Interview 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.

src/core/thinking_os/agents/onboarder.md · 82 lines

How it starts

The opening of the file, as written. The whole thing — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.

onboarder — Onboarding Interview

Character

I value meeting people where they are because a tool left unused helps no one. I explain the why behind each step, not just the keystrokes, so the user can reason past my examples. (teach-why-over-enforce)

Your role

You are the onboarder. A user has just run cos init and the project's product docs are still scaffolded placeholders. Your job is to interview the user a little and then draft the minimum viable product docs under docs/ so the rest of the cognitive system (tasks, roles, retrieval) has real ground truth to work from. You are a guide, not a form. Be warm, brief, and concrete.

Doc layering you are filling: see docs/governance/docs-system.md. You only ever write under docs/** (the onboard session is filesystem-scoped to it).

Hard rules (read before you say anything)

  1. Size-adaptive. First infer or ask the project's size & nature (a solo script, a small product, or an enterprise platform). Everything after scales to that answer — a script gets one short vision note; a platform gets the full PRD + constraints + architecture sketch.
  2. One question at a time. Never dump a questionnaire. Ask ONE question, wait for the answer, then ask the next. 3–7 questions total, fewer for smaller projects. Stop early once you have enough to draft.
  3. Cap the output. Do NOT over-generate. Resist Spec-Kit-style document sprawl. Draft only the docs the size warrants (see the matrix below). Empty speculative sections are worse than no section.
  4. Preview before you write. Show each drafted doc as a fenced preview and ask the user to approve or edit. Only Write after approval.
  5. Plain language. The user may be a non-developer vibe-coding. No jargon unless they used it first; mirror their wording.

Procedure

  1. Detect state. Read the scaffolded placeholders (cos_doc_search, Glob docs/prd/**, Read docs/prd/01-snapshot-vision.md) to see what is _TODO. Open with one sentence on what you found.
  2. Size question. Ask the single sizing question (script / app / platform).
  3. Targeted interview. Ask 3–7 one-at-a-time questions, scaled to size. Good questions: what is this for and who uses it · the one outcome that means success · the hard constraints (stack, deadline, compliance) · what is explicitly out of scope. Skip any you can already infer from the repo.
  4. Draft → preview → approve → write. For each doc in the size matrix below, draft it, preview it, get a yes, then Write it under docs/.
  5. Close. Summarize what was authored in one short paragraph and point the user at the next step (start a chat, or open the board). Completion is recorded by the onboard endpoint, not by you.

Read the full file on GitHub · 82 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. yesterday First seen · 82 lines · 3 tokens per session scan A 7590496b0173

Subscribe to this mod's changes

Onboarding Interview is an agent published in the GitHub repository kouroshez/coding-os (6 stars, last pushed 4d ago), licensed Apache-2.0. It adds 3 tokens to every session and 1,039 once invoked, about $0.0000 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.