quickstart

A fast onboarding command for startup founders that collects basic information about a product and its customers, then produces a first marketing or sales action.

In plain words
What is it for?
Use it to start marketing or sales work quickly, then use the full onboarding command when deeper business planning is needed.
Why use it?
It helps founders get a useful next step without completing a longer business interview first. It can reuse information already saved in the project's .anty files.

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/voxtechnologies/anty-framework/quickstart
Clone the repo
git clone --depth 1 https://github.com/VoxTechnologies/anty-framework
Per session 17 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,425 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 $0.00017 $0.01425
Opus 5 $0.00009 $0.00713
Sonnet 5 $0.00003 $0.00285
Haiku 4.5 $0.00002 $0.00143

Measured 2d ago against content hash 61cb7d93bea5, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

quickstart 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 2d 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

commands/quickstart.md · 175 lines

How it starts

The opening of the file, as written. The whole thing — 175 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/anty:quickstart — 5-Minute Quick Onboarding to First Action

Purpose

Get the founder from zero to their first actionable marketing/sales action in under 5 minutes. Collects only the minimum information needed to generate useful actions, then deepens context over time through progressive profiling.

This is NOT a replacement for /anty:onboard. It is a fast-track entry point:

  • /anty:quickstart → first action in 5 minutes, shallow context
  • /anty:onboard → full 14-topic business context, deep strategic planning

Before Starting

  1. Check if .anty/business-context.yaml already exists and is complete.

    • If complete: "Your full business context already exists. Running quickstart to generate your first action based on existing context." → Skip to Step 3 (Action Generation).
    • If partial: Read existing data, skip questions already answered, fill gaps with Steps 1-2.
    • If does not exist: Create .anty/ directory if needed, start from Step 1.
  2. Ensure .anty/config.yaml exists. Create with defaults if not.

Step 1: Core Question (1 question, covers Product + Target)

Ask ONE combined question:

"What does your product do, and who is it for? One or two sentences is enough."

Example answer: "AI tool that automates sales and marketing for startup founders who just launched their product."

From this single answer, extract:

  • product.description
  • product.problem_solved (infer from the product description)
  • target_market.ideal_customer

Echo back: "So [product] for [customer]. Got it."

Step 2: Channel Question (1 question)

"Where do your target customers spend time online? List the top 2-3 places."

Example answer: "HackerNews, Reddit, LinkedIn"

From this, extract:

  • target_market.customer_channels

Echo back: "Targeting [channels]. Clear."

Step 3: Action Generation (automatic, no question)

Based on the collected (or pre-existing) context, generate 3 concrete first actions. Each action must be:

  • Immediately executable (can be done today)
  • Specific (not "do marketing" but "post X on Y with Z angle")
  • Low-cost (time only, no paid spend)
  • Measurable (define what success looks like)

Read the full file on GitHub · 175 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. 2d ago First seen · 175 lines · 17 tokens per session scan A 61cb7d93bea5

Subscribe to this mod's changes

quickstart is a command published in the GitHub repository VoxTechnologies/anty-framework (6 stars, last pushed 4mo ago), licensed MIT. It adds 17 tokens to every session and 1,425 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 2026-08-31.