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 human-avatar/skills-for-humanity --skill s4h-aesthetic-pattern-detectiongit clone --depth 1 https://github.com/human-avatar/skills-for-humanityWrote 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/human-avatar/skills-for-humanity/s4h-aesthetic-pattern-detection)<a href="https://agentmods.dev/skills/human-avatar/skills-for-humanity/s4h-aesthetic-pattern-detection"><img src="https://agentmods.dev/badge/skills/human-avatar/skills-for-humanity/s4h-aesthetic-pattern-detection/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/human-avatar/skills-for-humanity/s4h-aesthetic-pattern-detection"><img src="https://agentmods.dev/badge/skills/human-avatar/skills-for-humanity/s4h-aesthetic-pattern-detection.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00082 | $0.01356 |
| Opus 5.5 | $0.00033 | $0.00542 |
| Sonnet 5.5 | $0.00016 | $0.00271 |
| Haiku 4.5 | $0.00008 | $0.00136 |
Grade A, and why
s4h-aesthetic-pattern-detection 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 1mo 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- aesthetic-pattern-detection — 97% identical, 8 lines differ
How it starts
The opening of the file, as written. The whole thing — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Aesthetic Pattern Detection
Surface features differ — colours, words, technologies, industries. Formal patterns recur across all of them. The same structural moves that make a symphony compelling make a strategy compelling. The same tension-and-resolution arc that drives a thriller drives a great pitch. Naming the pattern reveals options that surface-level analysis cannot, because once the pattern is named, its full playbook becomes available.
Your Process
Step 1: Describe the Thing What does it do and how does it feel to engage with it? Focus on behaviour and effect, not surface features — not "it uses blue and white" but "it creates calm authority that builds confidence incrementally." Describe the experience of it.
Framing check: Confirm the specific artefact before continuing. State what you've identified — the actual object being analyzed and its medium or domain — in one sentence, then use AskUserQuestion:
- Question: "I'm reading this as: [your one-sentence framing of the specific artefact and its context]. Is that right?"
- Header: "Framing"
- Options:
- Yes — proceed — framing is correct
- Adjust — one element is off; user will correct it before you continue
- Reframe — different artefact or context than read; incorporate the correction before proceeding
Step 2: Identify Formal Patterns Present Work through this list systematically — multiple patterns often operate simultaneously:
- Repetition/Rhythm — recurring elements that create expectation, then satisfy or productively subvert it
- Symmetry/Asymmetry — balance creates stability and trust; deliberate asymmetry creates tension and dynamism
- Hierarchy — clear ordering from most to least important, large to small, general to specific; guides attention
- Contrast — sharp differences that create definition, focus attention, and make meaning by comparison
- Tension/Resolution — a problem introduced and resolved, a question posed and answered; the engine of narrative
- Figure/Ground — a subject made vivid and clear by what surrounds and recedes
- Part/Whole — components that build into something greater than their sum
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.
- 1mo ago First seen · 125 lines · 82 tokens per session scan A 05fe46afcc7d
s4h-aesthetic-pattern-detection is a skill published in the GitHub repository human-avatar/skills-for-humanity (236 stars, last pushed 3mo ago), licensed MIT. It adds 82 tokens to every session and 1,356 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 2026-08-30.
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