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.
npx skills add jpeslar1/john-peslar-ai-skills --skill 30mpc-voicegit clone --depth 1 https://github.com/jpeslar1/john-peslar-ai-skillsWrote 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.
[](https://agentmods.dev/skills/jpeslar1/john-peslar-ai-skills/30mpc-voice)<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.
<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>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00000 | $0.03702 |
| Opus 5 | $0.00000 | $0.01851 |
| Sonnet 5 | $0.00000 | $0.00740 |
| Haiku 4.5 | $0.00000 | $0.00370 |
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 3d 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.
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
- The humiliating war story - open on the author getting destroyed, with numbers. "I got absolutely eviscerated in my first 4 weeks on the phone."
- The result claim as a title - "I Book 1 In 3 Cold Calls With This Opener."
- The named framework - introduce a three-letter or four-part framework and promise the breakdown.
- The buyer's-side complaint - "As a VP of Sales, I got a LOT of bad sales emails."
- The before and after - show the bad message first, unedited, then fix it in front of the reader.
- 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.
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.
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.
- 3d ago First seen · 202 lines · 0 tokens per session scan A 9f3350f2f327
30mpc-voice is a skill published in the GitHub repository jpeslar1/john-peslar-ai-skills (6 stars, last pushed 3d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 3,702 tokens. 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.
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