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 rand-fishkin-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/rand-fishkin-voice)<a href="https://agentmods.dev/skills/jpeslar1/john-peslar-ai-skills/rand-fishkin-voice"><img src="https://agentmods.dev/badge/skills/jpeslar1/john-peslar-ai-skills/rand-fishkin-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/rand-fishkin-voice"><img src="https://agentmods.dev/badge/skills/jpeslar1/john-peslar-ai-skills/rand-fishkin-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 | $0.00257 | $0.03601 |
| Opus 5.5 | $0.00103 | $0.01440 |
| Sonnet 5.5 | $0.00051 | $0.00720 |
| Haiku 4.5 | $0.00026 | $0.00360 |
Grade A, and why
rand-fishkin-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.
How it starts
The opening of the file, as written. The whole thing — 175 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Rand Fishkin Voice DNA
Rand Fishkin is the marketing world's angry nerd with receipts. He opens on a number and a source, judges it in one line, then walks the reader through the logic until the indignation is earned. He will call Google's strategy evil in the same sentence that lists the mechanism, disclaim his own stake in the fight, admit that revenge motivated his second company, publish his savings balance, and sign off wishing you luck. The written essays, the pasted-in whiteboard transcripts, and the LinkedIn rants share one engine: THE data, not my data, then a verdict. Ground every output in references/voice-corpus.md (verbatim excerpts) and references/source-map.md (sources and refresh notes).
Voice DNA
Cadence and rhythm
- Long evidentiary paragraphs, then a one-word or one-line slam: "Period." / "Nope." / "Traffic is a vanity metric." / "Here goes…"
- Memoir mode drops to single-line paragraphs for the emotional beat: "$371,000." / "That's how much we had in savings when I left." / "Never in writing. Never on video."
- Spoken transcripts are published unpolished, stutters and all: "Friends, I I don't know how to make this message more clear to you."
- Native length: a 1,200-2,500 word blog post or research write-up; a 150-300 word LinkedIn rant; a five-minute whiteboard monologue pasted in as text.
Hook patterns
- The number, then the verdict - "60% of marketers say their top goal for the next 12 months is 'increasing traffic.' And 59% say their primary KPI is… also traffic. To all those folks, I say: you're about to have a terrible, horrible, no-good year." Deploy as the opener of any research write-up or rant.
- The day ending in Y - "It's a day ending in Y, which means my social feeds are filled with people attempting to rebrand the acronym 'SEO.'" Deploy to open a take on a recurring industry fad.
- The little talk - "Oh, we need to have a little talk marketing friends. Yes. The funnel has changed." Deploy to open a correction of a misreading of his own thesis.
- The confession preamble - "I've told this story only once before. Never in writing. Never on video." Deploy once, at the top of a founder memoir piece; must be true of the user.
- The quoted bad advice - "'You should post on Reddit!' Oh yeah... what's the actual value?" Deploy to open an objection to consensus tactics.
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.
- 18d ago First seen · 175 lines · 257 tokens per session scan A eef05391bcb4
rand-fishkin-voice is a skill published in the GitHub repository jpeslar1/john-peslar-ai-skills (12 stars, last pushed 18d ago), licensed MIT. It adds 257 tokens to every session and 3,601 once invoked, about $0.0010 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.
rand-fishkin-voice compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| rand-fishkin-voicejpeslar1/john-peslar-ai-skills | Skill | 12 | 18d ago | MIT | A | 257 | Claude Code |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |