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 adenaufal/anti-slop-writing --skill indonesiangit clone --depth 1 https://github.com/adenaufal/anti-slop-writingWrote 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/adenaufal/anti-slop-writing/indonesian)<a href="https://agentmods.dev/skills/adenaufal/anti-slop-writing/indonesian"><img src="https://agentmods.dev/badge/skills/adenaufal/anti-slop-writing/indonesian/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/adenaufal/anti-slop-writing/indonesian"><img src="https://agentmods.dev/badge/skills/adenaufal/anti-slop-writing/indonesian.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 | $0.00065 | $0.09890 |
| Opus 5.5 | $0.00026 | $0.03956 |
| Sonnet 5.5 | $0.00013 | $0.01978 |
| Haiku 4.5 | $0.00006 | $0.00989 |
Grade A, and why
anti-slop-writing-id 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.
How it starts
The opening of the file, as written. The whole thing — 548 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Prinsip Utama
Versi 4.1 (27 September 2026): Panduan lintas model. Catatan model yang diperiksa pada versi 4.0 tetap ada di references/model-coverage.md; catatan itu bersifat historis, bukan klaim bahwa pola bahasa tertentu milik model tertentu.
Tulisan generik sering terasa aman, berulang, atau kurang terikat pada konteks. Revisi untuk memperjelas maksud, menambah detail yang memang tersedia, dan mempertahankan suara serta tujuan penulis. Jangan menganggap ketidaksempurnaan buatan sebagai bukti keaslian.
Panduan ini membantu menghasilkan tulisan yang jelas, spesifik, dan sesuai konteks. Variasi kalimat atau pilihan kata bukan cara yang terjamin untuk mengubah hasil detektor AI. Detektor bisa salah mengklasifikasikan teks manusia maupun teks berbantuan AI; jangan menjanjikan hasil tertentu.
Aturan lintas model
Tidak ada daftar ciri gaya yang berlaku pasti untuk semua versi atau semua jenis tugas. Model, pengaturan, prompt, dan konteks bisa mengubah hasil. Perlakukan pemeriksaan berikut sebagai heuristik editorial, bukan sidik jari yang terbukti secara statistik: cek apakah kalimat pembuka dan panjang kalimat terlalu berulang; apakah draf memakai kontras, daftar, transisi, atau ringkasan yang sama berulang kali; dan apakah kata-kata abstrak menggantikan fakta atau tindakan. Ubah hanya bagian yang mengganggu kejelasan, akurasi, atau suara yang diminta.
Saat menyunting, gunakan references/vocabulary-banlist.md dan references/structural-patterns.md sebagai pemicu pemeriksaan, bukan larangan tanpa konteks. Untuk keputusan tata bahasa dan ejaan Indonesia, ikuti rute ringkas di references/language-editing.md.
Pilih Tier Tone Dulu
Orang Indonesia nulis di tiga register yang cukup beda. Sebelum nulis, tentuin tier-nya. Default: semi-formal (kalau user nggak bilang apa-apa).
Tier 1: Formal
Untuk makalah akademis, laporan resmi, skripsi/tesis, dokumen kantor, dan jurnalisme. Kata ganti: saya, Anda (atau impersonal: peneliti, penulis). Utamakan bentuk lengkap seperti tidak. Partikel wacana (sih, dong, kan) dan code-switching ID-EN biasanya dihindari kecuali sesuai kutipan atau pedoman.
What ships with it
9 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.
- 1mo ago Changed · -24 lines b3acfb51ecb2
- 1mo ago Changed · -65 lines · -41 tokens per session 68bfa58cdbd0
- 1mo ago First seen · 637 lines · 106 tokens per session scan A 1f4b37332cb2
anti-slop-writing-id is a skill published in the GitHub repository adenaufal/anti-slop-writing (151 stars, last pushed 1mo ago), licensed MIT. It adds 65 tokens to every session and 9,890 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.
Other skills, from other repositories
ai-slop-detector
Universal prose audit. Scores writing on TWO axes — AI-Slop (does this read like AI wrote it?) and Comprehension (can a fresh reader follow this?). Use PROACTIVELY as a mandatory final QA pass on ANY prose generated for humans to read — every email (internal or external), proposal, report, status update, blog post…
humanizer-czech
Odstraň znaky AI-generovaného psaní z českého textu. Použij při editaci nebo revizi textu, aby zněl přirozeněji a lidštěji. Detekuje a opravuje 27 vzorců včetně: nafouklého významu, propagačního jazyka, anglického slovosledu, kalků, nominalizace, monotónního rytmu, nadužívání spojek, typických českých AI klišé…
shuorenhua
A writing and editing guide for making Chinese and English text sound natural and less machine-generated, with special attention to Taiwan Traditional Chinese usage. It preserves technical terms, facts, and the responsible subject.
simple-english
Rewrite text to ASD-STE100 Simplified Technical English.
whisper
Transcribe and translate speech in 99 languages.
website-maintainer
Use this skill when working on the Repomix documentation website in website/ directory, including VitePress configuration, multi-language content, or translation workflows.