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 regal-gentleman-barber-briefgit 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/regal-gentleman-barber-brief)<a href="https://agentmods.dev/skills/jpeslar1/john-peslar-ai-skills/regal-gentleman-barber-brief"><img src="https://agentmods.dev/badge/skills/jpeslar1/john-peslar-ai-skills/regal-gentleman-barber-brief/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/regal-gentleman-barber-brief"><img src="https://agentmods.dev/badge/skills/jpeslar1/john-peslar-ai-skills/regal-gentleman-barber-brief.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 | $0.00064 | $0.00735 |
| Opus 5.5 | $0.00026 | $0.00294 |
| Sonnet 5.5 | $0.00013 | $0.00147 |
| Haiku 4.5 | $0.00006 | $0.00073 |
Grade A, and why
regal-gentleman-barber-brief 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 — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Regal Gentleman-Inspired Barber Brief
Use this skill when the decision is less about trends and more about the conversation in the barber chair. It is an independent interpretation of Regal Gentleman's public transformation and education content. It does not claim to be a particular barber's opinion. Read the source map when current source context or attribution is needed.
Core lens
A useful haircut recommendation has to translate into a result a barber can execute. Reference photos are helpful only when they show a realistic match for texture, density, and starting length. Name the shape, the retained length, the transition, and the growth path.
Treat large changes as a sequence when possible. A cut can make the present look sharper while leaving enough length to grow into the next option.
Use this skill for
- Preparing for a barber appointment
- Moving from long or overgrown hair to a controlled medium or short style
- Deciding between a taper, fade, scissor-led cut, or a length-preserving clean-up
- Choosing and annotating reference photos
Workflow
- Define the starting point and commitment level: maintenance interval, how much length is safe to lose, styling ability, and whether a future grow-out matters.
- Separate the decision into top, sides, corners, crown, neckline, fringe, and sideburns. Do not collapse it into “short sides, long top.”
- Create a barber brief in visible terms. If the client has good reference photos, explain exactly what each photo contributes and what should not be copied.
- Include a growth path. State how the cut should look at appointment day, two to four weeks, and when the next trim would be useful.
- Give a quick styling plan that makes the intended silhouette visible, plus a fallback for days without heat styling.
The brief must answer
- Where should the side transition begin and end?
- Is the desired result blended, disconnected, or scissor-led?
- Which areas should retain weight to avoid an overly round or overly severe profile?
- How should the fringe and crown move naturally?
- Is the neckline tapered, natural, or squared?
- What should the barber not take too short?
What ships with it
1 file 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 · 74 lines · 64 tokens per session scan A 8d3e91a55369
regal-gentleman-barber-brief is a skill published in the GitHub repository jpeslar1/john-peslar-ai-skills (12 stars, last pushed 18d ago), licensed MIT. It adds 64 tokens to every session and 735 once invoked, about $0.0003 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.
regal-gentleman-barber-brief compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| regal-gentleman-barber-briefjpeslar1/john-peslar-ai-skills | Skill | 12 | 18d ago | MIT | A | 64 | Claude Code |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
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| 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 |