AAS Core is a local control plane for coding agents that lets them search a large catalogue of skills, choose a stack, validate it, and create a reproducible plan. It is used to assemble and review agent workflows through its CLI, local MCP server, catalogue, plugins, and Workbench. The catalogue add-ons provide the skills, plugins, bundles, and workflows that AAS Core helps agents select and validate.
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 sickn33/agentic-awesome-skills --skill avoid-ai-writinggit clone --depth 1 https://github.com/sickn33/agentic-awesome-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/sickn33/agentic-awesome-skills/avoid-ai-writing)<a href="https://agentmods.dev/skills/sickn33/agentic-awesome-skills/avoid-ai-writing"><img src="https://agentmods.dev/badge/skills/sickn33/agentic-awesome-skills/avoid-ai-writing/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/sickn33/agentic-awesome-skills/avoid-ai-writing"><img src="https://agentmods.dev/badge/skills/sickn33/agentic-awesome-skills/avoid-ai-writing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk pass
- 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 | $0.00024 | $0.00567 |
| Opus 5 | $0.00012 | $0.00283 |
| Sonnet 5 | $0.00005 | $0.00113 |
| Haiku 4.5 | $0.00002 | $0.00057 |
Grade A, and why
avoid-ai-writing 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 6d 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
8 near-identical copies found in the catalogue:
- avoid-ai-writing — 100% identical, 0 lines differ
- avoid-ai-writing — 100% identical, 0 lines differ
- avoid-ai-writing — 100% identical, 0 lines differ
- avoid-ai-writing — 100% identical, 0 lines differ
- avoid-ai-writing — 100% identical, 0 lines differ
- avoid-ai-writing — 100% identical, 0 lines differ
- avoid-ai-writing — 100% identical, 0 lines differ
- avoid-ai-writing — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 45 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Avoid AI Writing — Audit & Rewrite
Detects and fixes AI writing patterns ("AI-isms") that make text sound machine-generated. Covers 21 pattern categories with a 43-entry word/phrase replacement table that maps each flagged term to a specific, plainer alternative.
When to Use This Skill
- When asked to "remove AI-isms," "clean up AI writing," or "make this sound less like AI"
- After drafting content with AI and before publishing
- When editing any text that sounds like it was generated rather than written
- When auditing documentation, blog posts, marketing copy, or internal communications for AI tells
What It Detects
21 pattern categories: formatting issues (em dashes, bold overuse, emoji headers, bullet-heavy sections), sentence structure problems (hedging, hollow intensifiers, rule of three), word/phrase replacements (43 entries like leverage→use, utilize→use, robust→reliable), template phrases, transition phrases, structural issues, significance inflation, copula avoidance, synonym cycling, vague attributions, filler phrases, generic conclusions, chatbot artifacts, notability name-dropping, superficial -ing analyses, promotional language, formulaic challenges, false ranges, inline-header lists, title case headings, and cutoff disclaimers.
Example
Prompt:
Audit this for AI writing patterns:
"In today's rapidly evolving AI landscape, developers are embarking on a pivotal journey to leverage cutting-edge tools that streamline their workflows. Moreover, these robust solutions serve as a testament to the industry's commitment to fostering seamless experiences."
Output: The skill returns four sections:
- Issues found — every AI-ism quoted (landscape, embarking, pivotal, leverage, cutting-edge, streamline, robust, serves as, testament to, fostering, seamless, Moreover, In today's rapidly evolving...)
- Rewritten version — "Developers are starting to use newer AI tools to simplify their work. These tools are reliable, and they're making development less painful."
- What changed — summary of edits
- Second-pass audit — re-reads the rewrite to catch any surviving tells
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.
- 6d ago First seen · 45 lines · 24 tokens per session scan A 33e0d1c7cb33
avoid-ai-writing is a skill published in the GitHub repository sickn33/agentic-awesome-skills (46,230 stars, last pushed yesterday), licensed MIT. It adds 24 tokens to every session and 567 once invoked, about $0.0001 per session on Opus 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 2026-09-05.
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