katelyn-bourgoin-voice

katelyn-bourgoin-voice is a skill for Claude Code from jpeslar1/john-peslar-ai-skills. It costs 207 tokens per session (3,843 once invoked), scanned A, original, MIT.

A writing guide for creating buyer-psychology teaching content, newsletters, and short hooks in a defined voice. It draws on Katelyn Bourgoin’s approach to explaining why people buy.

In plain words
What is it for?
Use it to draft newsletter issues, short-form marketing hooks, and lessons about customer behavior. It also points writers to source and example files for the voice.
Why use it?
It helps keep marketing lessons consistent, practical, and easy to read instead of academic or vague.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the voice-dna plugin — 79 skills shipped together

Good fit Use it to draft newsletter issues, short-form marketing hooks, and lessons about customer behavior. It also points writers to source and example files for the voice.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/jpeslar1/john-peslar-ai-skills/katelyn-bourgoin-voice
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 jpeslar1/john-peslar-ai-skills --skill katelyn-bourgoin-voice
Clone the repo
git clone --depth 1 https://github.com/jpeslar1/john-peslar-ai-skills

Made for: Claude Code.

Or install voice-dna, the plugin that ships this one along with the rest of its 79 skills.

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 katelyn-bourgoin-voice

README.md
[![agentmods](https://agentmods.dev/badge/skills/jpeslar1/john-peslar-ai-skills/katelyn-bourgoin-voice/github.svg)](https://agentmods.dev/skills/jpeslar1/john-peslar-ai-skills/katelyn-bourgoin-voice)
Your own site
<a href="https://agentmods.dev/skills/jpeslar1/john-peslar-ai-skills/katelyn-bourgoin-voice"><img src="https://agentmods.dev/badge/skills/jpeslar1/john-peslar-ai-skills/katelyn-bourgoin-voice/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for katelyn-bourgoin-voice

Your own site · 80×15
<a href="https://agentmods.dev/skills/jpeslar1/john-peslar-ai-skills/katelyn-bourgoin-voice"><img src="https://agentmods.dev/badge/skills/jpeslar1/john-peslar-ai-skills/katelyn-bourgoin-voice.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 207 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,843 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 $0.00207 $0.03843
Opus 5.5 $0.00083 $0.01537
Sonnet 5.5 $0.00041 $0.00769
Haiku 4.5 $0.00021 $0.00384

Measured 18d ago against content hash 24e7581e49d3, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

katelyn-bourgoin-voice 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 18d 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.

katelyn-bourgoin-voice/SKILL.md · 171 lines

How it starts

The opening of the file, as written. The whole thing — 171 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Katelyn Bourgoin Voice DNA

Katelyn Bourgoin is a four-time founder turned "customer whisperer," running Customer Camp and writing the Why We Buy newsletter, which translates behavioral economics and cognitive-bias research into short, applied marketing lessons. The voice is a friendly practitioner explaining a psychology trick she is still delighted by: an immersive second-person scene, the reveal of a named effect, a segmented list of how to use it today, and a warm sign-off. It is never academic and never abstract; every idea lands on a real brand, a real number, or a real tactic. Ground every output in references/voice-corpus.md (verbatim excerpts) and references/source-map.md (sources and refresh notes).

Voice DNA

Cadence and rhythm

  • Extremely short paragraphs, frequently one sentence long, with generous white space between them for scroll pacing.
  • Fixed five-part newsletter shape: cold-open stat or teaser, an "Imagine this..." second-person scene, the reveal of the named psychological effect, a "How To Apply This" section segmented by vertical, then "The Short of It" recap.
  • Second-person direct address almost throughout: "you," "your customers," "your buyers," rarely a distanced third person.
  • A rhetorical question is asked at the end of the scene, then answered one paragraph later once the effect is named.
  • Newsletter issues run roughly 600-900 words; short-form (X, LinkedIn) compresses the same shape into a single scene-plus-reveal.
  • Sentences inside a scene are short and declarative; complexity comes from stacking short sentences, not from subordinate clauses.

Hook patterns

  1. The "Did you know" stat tease - open cold with a surprising number and withhold the mechanism. "Your customers (and you) make ~35,000 decisions each day."
  2. The immersive second-person scene - a mini narrative in "you" voice that lands on the psychological question. The washer-repair, dinner-menu, and locksmith scenes in the corpus are all this move.
  3. The brand mystery - name a real brand or a high price and ask why it works before explaining. "Why do people eagerly spend $10,000+ for a Birkin bag?"
  4. The reveal-the-term hook - name the cognitive bias as a punchline right after the scene lands. "All the gear and no idea? Welcome to the Dunning-Kruger Effect."
  5. The self-aware confession hook - preempt reader overwhelm with a plain-spoken aside. "Before you start screaming into a pillow, let me share some good news."
  6. The outside-marketing analogy - reach for a story with nothing to do with business (Shackleton's 1913 recruiting ad) and then bring it back in one line: "You just need to modify one word."

Read the full file on GitHub · 171 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 18d ago Changed · +207 tokens per session 24e7581e49d3
  2. 1mo ago First seen · 171 lines · 0 tokens per session scan A 5d1b686e3cf5

Subscribe to this mod's changes

katelyn-bourgoin-voice is a skill published in the GitHub repository jpeslar1/john-peslar-ai-skills (12 stars, last pushed 18d ago), licensed MIT. It adds 207 tokens to every session and 3,843 once invoked, about $0.0008 per session on Opus 5.5. 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 2026-09-10.

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