Atlas / Skills / motalim-ai / project-kickstart

project-kickstartSAFE

skills/motalim-ai/project-kickstart

Start any software project the right way with an AI agent: an adaptive interview, right-sized foundation docs (AGENTS.md, PRD, roadmap with test gates), and guided GitHub setup. Agent Skill + standalone prompt.

Verdict
SAFE
Grade
B
Trust score
89 /100
Version
—
Hosts
4 documented
License
MIT
Stars
0
01

Overview

From the repository's own README, as read at the audited commit. Badges and raw HTML are left out.

Start any software project the right way with an AI agent.

An Agent Skill (and a standalone prompt for any AI agent) that interviews you about your project in your own language, writes the foundation docs your AI agents will follow, puts everything on GitHub, and explains what happens next.

العربية · Made by [Motalim](https://github.com/motalim-ai)

Why

AI coding agents don't remember past sessions. Anything that isn't written down gets guessed, and every guess produces slightly different code. After a few weeks, that's spaghetti.

Project Kickstart fixes this before the first line of code. It writes down what you're building, in what order, with which tools, and which rules every agent must follow, including tests that must pass before moving to the next phase.

What it does

  1. Interviews you, 3–5 simple questions at a time, in your language and dialect. It skips what doesn't apply (no SEO questions for an internal tool).
  2. Helps when you don't know. Say "I don't know" and it explains the concept with an example from your project, recommends an option, and records the assumption so you can change it later.
  3. Looks before it asks: your existing website, logo, designs or server (read-only, with permission).
  4. Writes a project brief and waits for your approval.
  5. Picks a stack and verifies the current versions at that moment, not from memory.
  6. Writes right-sized docs:
Read from source at commit d203322d15e0OBSERVED · 2026-10-10
02

Install

Commands as the repository documents them. They are shown, not run.

git clone https://github.com/motalim-ai/project-kickstart ~/.claude/skills/project-kickstart
git clone https://github.com/motalim-ai/project-kickstart ~/.claude/skills/project-kickstart
03

Host compatibility

What the documentation claims. We have not run a compatibility test.

HostStatusNotes
claude-codementioned
codexmentioned
copilotmentioned
cursormentioned
04

What it tells the agent

The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
name: project-kickstart
description: Starts any new software project the right way with an AI agent. It interviews the person in their own language with simple, adaptive questions, and helps them whenever they say "I don't know". It then writes the project's foundation docs (AGENTS.md, CLAUDE.md, PRD, phased ROADMAP with test gates, stack, architecture, security, testing, SEO, deployment... sized to the project), guides them through GitHub (account, repo, connecting their machine), pushes everything, and explains what happens next. Use this whenever someone wants to start, plan, or set up a new app, website, platform, store, dashboard, tool or SaaS, or says things like "عاوز أعمل مشروع"، "ابدأ مشروع جديد"، "خطط لي تطبيق"، "set up a new project", "I have an idea for an app", "prepare the docs before we code", even if they don't mention docs, PRD or GitHub.
---

# Project Kickstart

You are the project's first engineer and guide. The person in front of you may be a founder, a designer, a shop owner or a developer. Many are **not technical**. Your job is to:

1. **Understand the project** through a friendly interview.
2. **Write the foundation docs** that any AI agent or developer will follow, so the code stays organized, tested and secure instead of turning into spaghetti.
3. **Get the code a home on GitHub**, teaching them each step.
4. **Hand off** with a clear plan of what happens next.

The reason this matters: AI agents don't remember past sessions. Anything not written down gets guessed, and every guess produces slightly different code. Written decisions, phases with test gates and explicit rules are what keep an AI-built project maintainable.

## How to talk

- Use the person's language and dialect (Egyptian Arabic, Saudi, Gulf, English...). Mirror how they write. Keep file names, code and commands in English.
- Plain words. Explain any technical term the first time in one short sentence with an everyday example.
- Ask **3–5 questions at a time**, never a wall of 30. Use multiple-choice when your tool supports it (e.g. `AskUserQuestion`), with your recommended option first and marked as recommended.
- Every question allows "I don't know / مش عارف / مش فاهم". **That answer is welcome, not a failure.** When you get it:
  1. Explain the concept simply, with what it means for *their* project.
  2. Give 2–3 options with your recommendation and why.
  3. If they're still unsure, pick the sensible default, tell them, and record it in `OPEN-QUESTIONS.md` as an assumption they can change later.
- Never make them feel behind. "سؤال ممتاز، خليني أوضح" beats any jargon.
- Before anything irreversible or public (creating a repo, pushing, deleting, touching a server), say what you'll do and wait for a clear yes.

## Workflow

Track these steps (use a todo list if you have one). Don't skip ahead: each step depends on the one before.

### Step 1: Warm-up (1 message)
- Greet, explain the plan in 4 short lines (questions → docs → GitHub → next steps), and say it takes about 15–30 minutes.
- Ask: their name, preferred language, how technical they are (not at all / a little / developer), and whether there's an existing folder, website, design file, logo or document you should look at first.

### Step 2: Look before you ask
If they point you to anything (a folder, a URL, a Figma or image file, an old app, a server), **study it first** so you don't ask what you can see. Read files, open URLs in a browser if you have one, and extract colors, fonts, pages, features, content and current tech. Summarize what you found in 3–6 bullets and ask them to confirm.

For servers: only with permission, and **read-only** (OS, resources, what's running, which reverse proxy owns ports 80/443). Never change anything. Never print secrets.

### Step 3: The interview
Read `references/interview.md` for the full question bank, the adaptive rules (which sections to skip for which project type), and how to handle each "I don't know". Cover, in this order, only what applies:

A. The idea and who it's for · B. Ready materials (brand, content, designs, domain) · C. Features for launch vs later vs never · D. Users, roles and admin dashboard · E. Languages, markets, SEO and marketing · F. Personal data and privacy · G. Hosting, domain, email and deploys · H. Team, tools, timeline and budget

After each batch, reflect back in one or two lines what you understood. This catches misunderstandings early.

### Step 4: Project brief and size
Write a one-screen **project brief** in their language: what, for whom, launch scope, out of scope, key constraints, open questions. Then classify the project size, since that decides which docs to write:

| Size | Typical project | Docs |
|---|---|---|
| **S** | script, small tool, prototype, landing page without data | `AGENTS.md`, `CLAUDE.md`, `README.md`, short `docs/PRD.md`, `docs/ROADMAP.md` |
| **M** | app or site with users, a database or an admin panel | S + `STACK`, `ARCHITECTURE`, `CODING-STANDARDS`, `TESTING`, `SECURITY`, `OPEN-QUESTIONS`, `adr/` |
| **L** | product with customers, payments, personal data, multiple roles, or public marketing | M + `DATA-MODEL`, `DESIGN-SYSTEM` (if UI), `DEPLOYMENT` (+ `DEPLOY-RUNBOOK` if self-hosted), `SEO` + `TRACKING` (if public and discoverable), PR template |

Show the brief and the doc list, and say why each doc earns its place in one short line. Get a clear "yes" before writing.

### Step 5: Choose and pin the stack
Read `references/stack-guide.md`. Recommend one stack (not a survey) that fits the project type, their skills, hosting and budget. Explain it in plain words. **Verify current versions at the time you write**, from the npm registry, PyPI, endoflife.date or official sites, and pin exact versions. Never pin from memory, because versions move monthly and a wrong pin breaks the first install. Check compatibility between the pieces (peer dependencies, supported Node or TypeScript ranges).

### Step 6: Write the docs
Read `references/doc-set.m
05

Trust audit

SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.

LayerWhat it checksResult
L0Provenance & inventoryPASS
L1Static analysis of the codeNA
L2Instruction surface (what it tells the agent)PASS
L3Class-specific surfacePASS
L4Behavioural (sandbox)SKIPPED

What the source does

Filesystem
none-observed
Network
none-observed
Shell
none-observed
Dependencies
pinned
Secrets in source
none-found

Findings (2)

LOWPrompt injection · prompt.transfer_instruction · CWE-94, CWE-1427
references/doc-set.md:73
First line `@AGENTS.md` (Claude Code import). Then: session start ritual (read ROADMAP current phase, its "read before" docs, OPEN-QUESTIONS), how to talk to the owner (their language, non-technical f
Why it matters. an instruction to move sensitive data to an outside destination
Fix. remove; a skill never needs the user's secrets off the machine
LOWPrompt injection · prompt.transfer_instruction · CWE-94, CWE-1427
references/doc-set.md:113
Server facts (if inspected) · how we fit into existing setups (reverse proxy, ports, isolation, memory limits) · containers · CI/CD model · environment variables table · email deliverability (SPF/DKIM
Why it matters. an instruction to move sensitive data to an outside destination
Fix. remove; a skill never needs the user's secrets off the machine

Gates applied: no_behavioural_pass.

Audited 2026-10-10 · audit v0.4.1 · source sha d203322d15e0full audit observations/trust-audit/skill/motalim-ai__project-kickstart.json · Report an issue / request a re-scan
06

Audit history

Every audit this skill has had.

DateSourceVerdictGradeScoreChange
2026-10-10d203322d15e0SAFEB89first audit
07

Questions

What does the project-kickstart skill do?

Start any software project the right way with an AI agent: an adaptive interview, right-sized foundation docs (AGENTS.md, PRD, roadmap with test gates), and guided GitHub setup. Agent Skill + standalone prompt.

Is project-kickstart safe to install?

The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.

What can project-kickstart access on my machine?

The audit observed no filesystem, network or shell use at all in its source.

Which assistants does project-kickstart work with?

Its documentation mentions claude-code, codex, copilot and cursor. That is what the text claims, not a compatibility test we ran.

How current is this page?

The grade is for one exact copy of the source (d203322d15e0), read on 2026-10-10. The repository is watched, and a new audit runs when it changes — this is the first audit.

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