package-json-modification-protection
关于
This Claude Skill protects specific lines in package.json files that are marked with a "Do not touch this line Cursor" comment from being modified. It automatically enforces this rule during code reviews and when writing new code, ensuring critical configurations remain unchanged. Developers should use it to safeguard essential dependencies or version pins in their project's package.json.
快速安装
Claude Code
推荐npx skills add oimiragieo/agent-studio -a claude-code/plugin add https://github.com/oimiragieo/agent-studiogit clone https://github.com/oimiragieo/agent-studio.git ~/.claude/skills/package-json-modification-protection在 Claude Code 中复制并粘贴此命令以安装该技能
GitHub 仓库
Frequently asked questions
What is the package-json-modification-protection skill?
package-json-modification-protection is a Claude Skill by oimiragieo. Skills package instructions and resources that Claude loads on demand, so Claude can perform package-json-modification-protection-related tasks without extra prompting.
How do I install package-json-modification-protection?
Use the install commands on this page: add package-json-modification-protection to Claude Code as a plugin, or clone its repository into your skills directory, then restart Claude so it picks up the skill.
What category does package-json-modification-protection belong to?
package-json-modification-protection is in the Other category, tagged general.
Is package-json-modification-protection free to use?
Yes. package-json-modification-protection is listed on AIMCP and free to install. It runs inside Claude, so no separate service account is required to use the skill itself.
相关推荐技能
LlamaGuard是Meta推出的7-8B参数内容审核模型，专门用于过滤LLM的输入和输出内容。它能检测六大安全风险类别（暴力/仇恨、性内容、武器、违禁品、自残、犯罪计划），准确率达94-95%。开发者可通过HuggingFace、vLLM或Sagemaker快速部署，并能与NeMo Guardrails集成实现自动化安全防护。
这个Claude Skill帮助开发者优化云成本，通过资源调整、标记策略和预留实例来降低AWS、Azure和GCP的开支。它适用于减少云支出、分析基础设施成本或实施成本治理策略的场景。关键功能包括提供成本可视化、资源规模调整指导和定价模型优化建议。
该Skill为开发者提供体育博彩数据分析工具，可分析盘口、大小球和特殊投注，识别价值投注机会。它整合历史数据和情景统计，生成包含时间戳的结构化Markdown报告。适用于需要快速获取博彩市场洞察的娱乐或教育类应用开发。
这个Skill使用bitsandbytes库量化大语言模型，能在GPU内存有限时通过8位或4位量化减少50-75%内存占用，同时保持精度损失最小。它支持INT8、NF4、FP4等多种量化格式，可与HuggingFace Transformers无缝集成，适用于需要部署更大模型或加速推理的场景。还提供QLoRA训练和8位优化器支持，让开发者能轻松实现高效模型压缩。