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30mpc-voice

30mpc-voice is a skill for Claude Code from jpeslar1/john-peslar-ai-skills. It costs 217 tokens per session (3,703 once invoked), scanned A, original, MIT.

A sales-script writing guide inspired by 30 Minutes to President's Club. It focuses on the exact words used in cold calls, cold emails, objection replies, and other sales conversations.

In plain words
What is it for?
Use it to draft cold-call openings, cold emails, objection responses, sales talk tracks, and practical script checklists.
Why use it?
It turns broad sales advice into wording a seller can use and review. Before-and-after examples help show how a message or talk track changes.

Skill for Claude Code

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

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

not rated 12repo +1 changed 18d ago A scan 217 tokens original MIT

Good fit Use it to draft cold-call openings, cold emails, objection responses, sales talk tracks, and practical script checklists.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/jpeslar1/john-peslar-ai-skills/30mpc-voice
View source ↗ jpeslar1/john-peslar-ai-skills
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 30mpc-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 30mpc-voice

README.md
[![agentmods](https://agentmods.dev/badge/skills/jpeslar1/john-peslar-ai-skills/30mpc-voice/github.svg)](https://agentmods.dev/skills/jpeslar1/john-peslar-ai-skills/30mpc-voice)
Your own site
<a href="https://agentmods.dev/skills/jpeslar1/john-peslar-ai-skills/30mpc-voice"><img src="https://agentmods.dev/badge/skills/jpeslar1/john-peslar-ai-skills/30mpc-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 30mpc-voice

Your own site · 80×15
<a href="https://agentmods.dev/skills/jpeslar1/john-peslar-ai-skills/30mpc-voice"><img src="https://agentmods.dev/badge/skills/jpeslar1/john-peslar-ai-skills/30mpc-voice.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 217 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,703 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 $0.00217 $0.03703
Opus 5.5 $0.00087 $0.01481
Sonnet 5.5 $0.00043 $0.00741
Haiku 4.5 $0.00022 $0.00370

Measured 18d ago against content hash 29b7ee19d028, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

30mpc-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.

30mpc-voice/SKILL.md · 202 lines

How it starts

The opening of the file, as written. The whole thing — 202 lines — stays where its author put it; the contents beside it link to each section on GitHub.

30MPC Voice DNA

30 Minutes to President's Club is the tactics desk of B2B sales. Armand Farrokh and Nick Cegelski publish one thing over and over: the exact words to say, the reason they work, and a before-and-after that proves it. Nothing is strategic, nothing is aspirational, and nothing ships without a script. The register is peer-to-peer, funny, slightly profane, and allergic to anything a seller cannot use on the next call. Ground every output in references/voice-corpus.md (verbatim excerpts) and references/source-map.md (sources and refresh notes).

Voice DNA

Cadence and rhythm

  • Short expository sentences broken by scripts. The script is always visually separated and always in the seller's actual spoken words.
  • Structure is fixed: the pain the reader recognises, the tactic named, the numbered breakdown, the script, the before-and-after, the checklist.
  • Frameworks are three or four ingredients with alliterative or memorable names. Trigger, Tension, Trust. Personalization, Problem, Solution, CTA.
  • A war story opens most pieces and it carries dial counts and meeting counts. "800 dials, 0 meetings booked in 4 weeks."
  • Asides in parentheses do the joking so the body stays tactical.

Hook patterns

  1. The humiliating war story - open on the author getting destroyed, with numbers. "I got absolutely eviscerated in my first 4 weeks on the phone."
  2. The result claim as a title - "I Book 1 In 3 Cold Calls With This Opener."
  3. The named framework - introduce a three-letter or four-part framework and promise the breakdown.
  4. The buyer's-side complaint - "As a VP of Sales, I got a LOT of bad sales emails."
  5. The before and after - show the bad message first, unedited, then fix it in front of the reader.
  6. The data slap - a number from a call-recording study used to settle an argument about phrasing.

Lexicon

  • Signature vocabulary: talk track, opener, trigger, tension, problem language, permission, multithread, discovery, cut through, book the meeting, tear down, tactic, rep, dials, sequence.
  • Framework names in the wild: Triple T, the reply method, minimum viable discovery, trade don't discount.
  • Casual peer register with mild profanity and self-mockery. "What the hell do you actually do?" "Let's tear 'em down."
  • Buyer-side sensory language is prized: "logging into hundreds of 2FA windows", "running to the bank at 11pm". They call this triggering the prospect.
  • Anti-buzzword list stated openly: single source of truth, all-in-one platform, AI-powered.

Read the full file on GitHub · 202 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 · +217 tokens per session 29b7ee19d028
  2. 1mo ago First seen · 202 lines · 0 tokens per session scan A 9f3350f2f327

Subscribe to this mod's changes

30mpc-voice is a skill published in the GitHub repository jpeslar1/john-peslar-ai-skills (12 stars, last pushed 18d ago), licensed MIT. It adds 217 tokens to every session and 3,703 once invoked, about $0.0009 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 2026-09-09.

Marketing and SEOWriting and docs
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30mpc-voice next to 6 skills from other repositories
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