morgan-j-ingram-voice

morgan-j-ingram-voice is a skill for Claude Code from jpeslar1/john-peslar-ai-skills. It costs 272 tokens per session (4,184 once invoked), scanned A, original, MIT.

A writing guide for sales prospecting content in a style inspired by Morgan J Ingram, a sales coach and author. It lays out named tactics, timings, measured results, and answers to common objections.

In plain words
What is it for?
Use it for cold-call scripts, LinkedIn voice-note and video advice, and training posts for sales development representatives, or SDRs.
Why use it?
It helps turn sales advice into specific steps rather than broad encouragement. Readers can see what to say, when to say it, and how the writer supports the recommendation.

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 for cold-call scripts, LinkedIn voice-note and video advice, and training posts for sales development representatives, or SDRs.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/jpeslar1/john-peslar-ai-skills/morgan-j-ingram-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 morgan-j-ingram-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 morgan-j-ingram-voice

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

Your own site · 80×15
<a href="https://agentmods.dev/skills/jpeslar1/john-peslar-ai-skills/morgan-j-ingram-voice"><img src="https://agentmods.dev/badge/skills/jpeslar1/john-peslar-ai-skills/morgan-j-ingram-voice.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 272 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,184 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 $0.00272 $0.04184
Opus 5.5 $0.00109 $0.01674
Sonnet 5.5 $0.00054 $0.00837
Haiku 4.5 $0.00027 $0.00418

Measured 17d ago against content hash 2d8706e40d48, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

morgan-j-ingram-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 17d 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.

morgan-j-ingram-voice/SKILL.md · 172 lines

How it starts

The opening of the file, as written. The whole thing — 172 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Morgan J Ingram Voice DNA

Morgan J Ingram is the whiteboard coach of top-of-funnel sales: cold calls, LinkedIn voice notes, prospecting videos, and the SDR role itself. He names every tactic (PLA, PAQ, 10-30-10), gives it a timing to the half-second, proves it with a number he measured himself, and stages the reader's pushback in their own words before answering with a flat "Yes" or "It works." His failures are his credentials, told in short lines and closed with an emoji. 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 declaratives, one per line, light on subordinate clauses: "I was fed up." / "Try this out. It works." / "Boy, was I wrong." Median sentence around nine words.
  • A label or a question opens, the body answers in 4-10 lines, a question to the room closes. Roughly 70 percent of post lines are a single sentence.
  • Frameworks arrive as a name, an expansion, and a timing: "Framework: 10-30-10. 10 seconds: Reason for my video. 30 seconds: Value proposition. 10 seconds: Call to action."
  • The pushback is quoted, then flipped in one breath: "Is it harder than it used to be? Yes. Is it completely dead? No."
  • Long-form (HubSpot) keeps the rhythm and adds friendly fillers: "folks," "I know, big shocker," "That's just not it," "You are reading that correctly.. 5-10 a year."
  • Native length: a 60-150 word LinkedIn post, often the caption of his own coaching video; a 2,000-2,500 word numbered column for long form.
  • Spoken (items 101-110, one podcast), sentences stretch to 20-40 words chained on 'and', 'so', and 'like', but the frame holds: a named three-part framework ('URL to IRL... gotta catch them all'), a number stated as data ('I'm not saying doom and gloom, I'm just giving you the data'), and a warm one-line opener ('Excited to be here, man. Excited to chop it up.').

Hook patterns

  1. The labelled tip - a capitalized label, a colon, then the tactic in one sentence: "COLD CALLING TIP: Start leaving frictionless voicemails." / "Prospecting Tip: If you are looking to build pipeline this week. Do five personalized emails and five personalized videos." Deploy as line one of any tactical post.
  2. The staged objection - the reader's pushback in their own words, with the emoji: "'Yeah.. but I'm just an SDR' 😳" / "PRACTICE?! Hold up Morgan.. I don't have time for practice.." Deploy to open a mindset or discipline post.
  3. The rejection letter - a quoted verdict against him, then the scene: "'Sorry, Morgan, we like you as a content creator. However, your format and style did not pass the final production cut.' I sat in the airport, devastated." Deploy to open a lesson earned by failure.
  4. The secret - a permission question: "Can I share a secret? Video isn't only used for prospecting." Deploy to widen a tactic the reader thinks is narrow.
  5. The struggle question - name the pain as a question: "Struggling with your cold calling intro?" Deploy to open a how-to post or video caption.
  6. The analogy opener - a plain comparison from the gym or the court: "Prospecting is like working out." / Kobe hitting jumpers because "he practices every single day." Deploy to open a consistency post.

Read the full file on GitHub · 172 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. 17d ago Changed · +1 lines 2d8706e40d48
  2. 18d ago First seen · 171 lines · 272 tokens per session scan A d12501b06137

Subscribe to this mod's changes

morgan-j-ingram-voice is a skill published in the GitHub repository jpeslar1/john-peslar-ai-skills (12 stars, last pushed 18d ago), licensed MIT. It adds 272 tokens to every session and 4,184 once invoked, about $0.0011 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 2026-10-19.

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