Claude Scholar is a semi-automated research assistant for academic research and software development, supporting literature review, coding, experiments, reporting, writing, and project knowledge management. Computer science and AI researchers use it across the research workflow with several coding-agent platforms; the catalogue contains its skills, commands, agents, hooks, plugin, and instruction.
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 Galaxy-Dawn/claude-scholar --skill writing-anti-aigit clone --depth 1 https://github.com/Galaxy-Dawn/claude-scholarWrote 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/galaxy-dawn/claude-scholar/writing-anti-ai)<a href="https://agentmods.dev/skills/galaxy-dawn/claude-scholar/writing-anti-ai"><img src="https://agentmods.dev/badge/skills/galaxy-dawn/claude-scholar/writing-anti-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/galaxy-dawn/claude-scholar/writing-anti-ai"><img src="https://agentmods.dev/badge/skills/galaxy-dawn/claude-scholar/writing-anti-ai.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- 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 | $0.00105 | $0.02276 |
| Opus 5 | $0.00053 | $0.01138 |
| Sonnet 5 | $0.00021 | $0.00455 |
| Haiku 4.5 | $0.00011 | $0.00228 |
Grade A, and why
writing-anti-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 9d 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 — 230 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Writing Anti-AI
Remove AI-generated writing patterns from text to make it sound natural and human-written. Supports both English and Chinese.
Overview
This skill identifies and eliminates predictable AI writing patterns from prose, based on Wikipedia: Signs of AI writing, maintained by WikiProject AI Cleanup.
Core insight: LLMs use statistical algorithms to predict what should come next. The result tends toward the most statistically likely outcome that applies to the widest variety of cases—creating detectable patterns.
When to Use This Skill
Trigger phrases:
- "Humanize this text" / "人性化处理这段文字"
- "Remove AI writing patterns" / "去除 AI 写作痕迹"
- "Make this sound more natural" / "让这段文字更自然"
- "This sounds robotic/AI-generated" / "这听起来像机器写的"
- "Fix the AI patterns" / "修复 AI 模式"
Use cases:
- Editing AI-generated content to sound human
- Reviewing text for AI patterns before publication
- Polishing academic or professional writing
- Removing "slop" from prose
Core Rules (快速检查清单)
1. Cut Filler Phrases
Remove throat-clearing openers and emphasis crutches.
English examples:
- "In order to achieve this goal" → "To achieve this"
- "Due to the fact that" → "Because"
- "It is important to note that" → (delete)
中文示例:
- "为了实现这一目标" → "为了实现这一点"
- "值得注意的是" → (删除)
- "基于……的事实" → "因为"
2. Break Formulaic Structures
Avoid binary contrasts, dramatic fragmentation, rhetorical setups.
Patterns to avoid:
- Negative parallelisms: "It's not just X, it's Y"
- Rule of three: "A, B, and C" (prefer two or four items)
- Em-dash reveals: "X—Y" (just use commas)
3. Vary Rhythm
Mix sentence lengths. End paragraphs differently.
Check:
- Three consecutive sentences same length? Break one.
- Paragraph ends with punchy one-liner? Vary it.
4. Trust Readers
State facts directly. Skip softening, justification, hand-holding.
Bad: "It could potentially be argued that the policy might have some effect." Good: "The policy may affect outcomes."
What ships with it
6 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.
- 9d ago First seen · 230 lines · 105 tokens per session scan A b86ea0c27159
writing-anti-ai is a skill published in the GitHub repository Galaxy-Dawn/claude-scholar (5,431 stars, last pushed 16d ago), licensed MIT. It adds 105 tokens to every session and 2,276 once invoked, about $0.0005 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 2026-09-03.
Other skills, from other repositories
stss
Reduce defensive disclaimers, stacked hedging, and self-protective narration in proposals and decision-facing writing. Use when the user asks to rewrite or audit a proposal, plan, research contribution, executive summary, or similar text for directness. Do not use for ordinary code work or unrelated prose.
research
Performs deep research on a topic via deepresearch. Simulates a multi-step research process and returns a comprehensive research result as a string.
intuitive-preflight
Turn a vague task, plan, issue, or "LGTM/go ahead" request into an approval-ready preflight contract before implementation starts. Use when the user wants prompt preflight, clearer scope, non-goals, context package, acceptance criteria, definition of done, verification, stop gates, the exact execution command, or…
do-it-core
Use when repository work needs a shared baseline for intent, facts, causal changes, and honest evidence.
do-it-handbook
Use when repeated rediscovery of stable project knowledge makes a small shared handbook useful.
do-it-context
Use when project terms, relationships, or invariants drift between user language, docs, and implementation.