Borrowing it
Nothing to install: this file belongs to Railly/agent-brain. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Railly/agent-brain/main/.agents/skills/de-ai/SKILL.mdgit clone --depth 1 https://github.com/Railly/agent-brainWrote 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/railly/agent-brain/de-ai)<a href="https://agentmods.dev/skills/railly/agent-brain/de-ai"><img src="https://agentmods.dev/badge/skills/railly/agent-brain/de-ai/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/railly/agent-brain/de-ai"><img src="https://agentmods.dev/badge/skills/railly/agent-brain/de-ai.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 | $0.00013 | $0.00495 |
| Opus 5.5 | $0.00005 | $0.00198 |
| Sonnet 5.5 | $0.00003 | $0.00099 |
| Haiku 4.5 | $0.00001 | $0.00049 |
Grade A, and why
de-ai 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 2mo 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.
What it actually says
De-AI-ify text: $ARGUMENTS
IMPORTANT: Be direct
- Read file, create -HUMAN version, apply changes
What Gets Removed
Overused Transitions
- "Moreover," "Furthermore," "Additionally," "Nevertheless"
- Excessive "However" usage
- "While X, Y" openings
AI Clichés
- "In today's fast-paced world"
- "Let's dive deep"
- "Unlock your potential"
- "Harness the power of"
- "Game-changer"
- "Cutting-edge"
Hedging Language
- "It's important to note"
- "It's worth mentioning"
- Vague quantifiers: "various," "numerous," "myriad"
Corporate Buzzwords
- "utilize" → "use"
- "facilitate" → "help"
- "optimize" → "improve"
- "leverage" → "use"
- "streamline" → "simplify"
- "robust" → "strong"
Robotic Patterns
- Rhetorical questions + immediate answers
- Obsessive parallel structures
- Always exactly three examples
- "Let me explain..."
What Gets Added
- Varied sentence lengths
- Conversational tone
- Direct statements
- Confident assertions
- Natural rhythm
Flow
- Read original file at $ARGUMENTS
- Create copy:
{filename}-HUMAN.md - Apply de-AI-ification
- Output change log
Example
Before (AI): "In today's rapidly evolving digital landscape, it's crucial to understand that leveraging AI effectively isn't just about utilizing cutting-edge technology. It's about harnessing its transformative potential."
After (Human): "AI works best when you use it for specific tasks. Focus on what it does well: writing code, analyzing data, answering questions."
Output
Created: {filename}-HUMAN.md
Changes:
- Removed 3 AI clichés
- Simplified 5 corporate buzzwords
- Shortened 2 run-on sentences
- Added direct statements
Manual review needed:
- Line 15: needs specific example
- Line 42: vague claim, add data
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.
- 2mo ago First seen · 83 lines · 13 tokens per session scan A faa1fef32b9c
de-ai is a skill published in the GitHub repository Railly/agent-brain (22 stars, last pushed 3mo ago), licensed MIT. It adds 13 tokens to every session and 495 once invoked, about $0.0001 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.
de-ai compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| de-aiRailly/agent-brain | Skill | 22 | 3mo ago | MIT | A | 13 | 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 |