minimum-viable-audience

minimum-viable-audience is a skill for Claude Code, Codex from deciqAI/knowledge-skills. It costs 87 tokens per session (660 once invoked), scanned A, original, MIT.

A positioning method that chooses the smallest specific group of people whose problem a product can solve exceptionally well. It treats a target audience as real people with shared needs and habits, not just a broad demographic.

In plain words
What is it for?
Use it to choose an initial market, define a niche, improve word of mouth, or focus a creator, small business, or early product.
Why use it?
It prevents vague “everyone is a customer” positioning that often produces a product nobody strongly prefers or recommends.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to choose an initial market, define a niche, improve word of mouth, or focus a creator, small business, or early product.

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Install with agentmods
npx agentmods add skills/deciqai/knowledge-skills/minimum-viable-audience
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 deciqAI/knowledge-skills --skill minimum-viable-audience
Clone the repo
git clone --depth 1 https://github.com/deciqAI/knowledge-skills

Made for: Claude Code, Codex.

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.

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README.md
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Per session 87 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 660 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 $0.00087 $0.00660
Opus 5 $0.00044 $0.00330
Sonnet 5 $0.00017 $0.00132
Haiku 4.5 $0.00009 $0.00066

Measured 9d ago against content hash 76d43de9c1d1, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

minimum-viable-audience 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 9d 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.

minimum-viable-audience/SKILL.md · 44 lines

How it starts

The opening of the file, as written. The whole thing — 44 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Minimum Viable Audience — Win a Small Specific Group First

Overview

The Minimum Viable Audience (Seth Godin) is the smallest group of people whose problem you can solve so well they tell others — the deliberate opposite of appealing to everyone. Specificity is the strategy: a tight audience lets you make something remarkable, and remarkable travels. Trying to serve everyone produces something no one loves.

When to Use

  • "Everyone is our customer" thinking
  • Weak word-of-mouth / bland positioning
  • Creators, indie products, and SMBs with no ad budget who need organic spread

The Process

  1. Name a specific person, not a demographic — worldview, where they gather, what they already believe.
  2. Size the smallest audience that sustains you (revenue ÷ per-customer value = the number you actually need). Gate: if the number is "millions to survive," the model, not the audience, is the problem.
  3. Make something they'd miss if it vanished — remarkable to them, not to the average person.
  4. Show up where they already are; earn attention by being the best answer for that group.
  5. Engineer word-of-mouth: give them a reason and the language to tell peers. Gate: if it isn't share-worthy to this group, tighten the audience or the offer.
  6. Expand only after saturation — adjacent audiences, once the core loves it.

Applying It Well

  • "Smaller" feels scary but concentrates limited resources where they compound.
  • Better to be loved by 1,000 than tolerated by 100,000.
  • Positioning, product, and channel all sharpen once the person is specific.

Red Flags

  • Broadening the audience to feel safer (dilutes everything).
  • Defining the audience by demographics instead of worldview.
  • No mechanism for the core to spread the word.

Verification

  • A specific person (worldview + gathering place) named
  • Survival audience size computed and realistic
  • Offer is remarkable to that exact group
  • A word-of-mouth trigger designed in

Read the full file on GitHub · 44 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. 9d ago First seen · 44 lines · 87 tokens per session scan A 76d43de9c1d1

Subscribe to this mod's changes

minimum-viable-audience is a skill published in the GitHub repository deciqAI/knowledge-skills (10 stars, last pushed 11d ago), licensed MIT. It adds 87 tokens to every session and 660 once invoked, about $0.0004 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.

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