persona

A command for creating a buyer persona, a practical description of the people or organizations most likely to buy a product, using the Jobs-to-be-Done framework.

In plain words
What is it for?
Use it to define an ideal customer, enter a new market, improve messaging, align marketing with sales, or plan content around buyers' needs and purchasing journey.
Why use it?
It helps teams understand what buyers are trying to accomplish, what worries them, and how they decide, beyond basic age or job-title details.

Command

Part of the everything-claude-marketing plugin — 15 skills, 22 commands, 18 agents, 2 hooks shipped together

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/brainbytes-dev/everything-claude-marketing/persona
Clone the repo
git clone --depth 1 https://github.com/brainbytes-dev/everything-claude-marketing

Or install everything-claude-marketing, the plugin that ships this one along with the rest of its 15 skills, 22 commands, 18 agents, 2 hooks.

Per session 27 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,896 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 $0.00027 $0.01896
Opus 5 $0.00014 $0.00948
Sonnet 5 $0.00005 $0.00379
Haiku 4.5 $0.00003 $0.00190

Measured 2d ago against content hash 63932e0dd554, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

persona 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.

commands/persona.md · 183 lines

How it starts

The opening of the file, as written. The whole thing — 183 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/persona

Create a detailed, actionable buyer persona grounded in the Jobs-to-be-Done framework — not a fictional character sheet, but a strategic tool for decision-making.

What This Command Does

This command builds a comprehensive buyer persona that goes beyond surface-level demographics. Using the Jobs-to-be-Done (JTBD) framework, it identifies the functional, emotional, and social jobs your target buyer is trying to accomplish, along with the pain points, desired outcomes, and decision criteria that drive their purchasing behavior. The persona includes demographic and firmographic context, psychographic insights, media consumption habits, objection patterns, and a mapped buying journey with key influence points. The result is a living document that marketing, sales, product, and customer success teams can all use.

When to Use

  • Launching a new product and defining your ideal customer profile
  • Entering a new market segment or vertical
  • Refining messaging that is not resonating with your target audience
  • Aligning marketing and sales on who you are actually selling to
  • Building content strategy and need to understand audience deeply
  • Preparing for a brand refresh or repositioning
  • Onboarding new marketing or sales team members who need customer context
  • Creating ad targeting criteria and lookalike audiences

How It Works

  1. Gathers inputs — Asks about your product, market, existing customer data, and any hypotheses about your target buyer
  2. Defines the JTBD — Identifies the primary functional, emotional, and social jobs the buyer is hiring your product to do
  3. Builds demographics — Establishes role, seniority, company size, industry, and firmographic context
  4. Maps psychographics — Defines motivations, frustrations, values, and decision-making style
  5. Identifies pain points — Catalogs specific problems the buyer faces and how they currently solve them
  6. Charts the buying journey — Maps the stages from problem recognition through vendor selection
  7. Documents objections — Lists common objections and the underlying concerns behind them
  8. Profiles media habits — Identifies where the buyer consumes information, who they trust, and how they evaluate solutions

Read the full file on GitHub · 183 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 · 183 lines · 27 tokens per session scan A 63932e0dd554

Subscribe to this mod's changes

persona is a command published in the GitHub repository brainbytes-dev/everything-claude-marketing (5 stars, last pushed 5mo ago), licensed MIT. It adds 27 tokens to every session and 1,896 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.